Alternatives to Stackable

Create stunning, professional websites swiftly with Stackable’s lightweight and feature-rich blocks. Stackable offers all the essential tools for web design and more, ensuring that whether you are a web designer, an agency, a blogger, or just starting out, you can elevate your web design projects. With our pre-designed templates and user-friendly page-building features, you can confidently craft websites that look polished and professional. This platform enables you to expand your client base and deliver high-quality results quickly, efficiently, and effectively. Streamline your content production and enhance your visibility with blocks tailored for blogging and content marketing. Transform your creative ideas into reality and provide significant value to your clients, even if you lack coding skills. Stackable has powered the design of over 150,000 stunning and lightning-fast websites. Regardless of your industry, our array of pre-built designs, comprehensive block library, and UI Kits give you the tools to maximize your WordPress capabilities. Discover the design that perfectly aligns with your vision, your business needs, or your clients’ requirements, and watch your projects thrive. With Stackable, the possibilities for innovative web design are endless.

Hiro serves as a client-server library designed to enhance the Nakama game server, enabling developers to seamlessly incorporate various economy, social, and LiveOps functionalities into their games. This library is accessible in several formats, including a C# version for Unity Engine, a C++ variant for Unreal Engine, and a server package that harmonizes with the game server. Hiro provides a robust array of tested metagame features that can be swiftly integrated, thus allowing developers to prioritize the essence of gameplay. Developers can establish base and loot table rewards for players, facilitate purchases using either soft or real currency, and create stackable or consumable game items. It also supports the initialization and management of multiple currencies within the game's economic framework. Furthermore, Hiro allows for the customization of store bundles and offer walls according to player behaviors while enabling personalized experiences through experiments. Live events can be scheduled, giving players opportunities to engage and earn unique rewards, and timed or scored events can also be initiated, inviting players to request and share their inventories with others. By utilizing Hiro, game developers can significantly enhance player engagement through these dynamic features.

Propertybook NYC stands as the premier platform for real estate data in New York City. As a top-tier research tool, it offers unparalleled data to industry professionals, enabling them to make swift and informed decisions. We meticulously monitor every property, condominium, and cooperative in NYC, guaranteeing that our clients receive the most precise and current property and sales information. Our innovative stackable map layers enhance research capabilities, providing immediate geospatial insights that are essential for effective analysis. Real estate professionals—including appraisers, brokers, developers, investors, property owners, lenders, and attorneys—rely on Propertybook to guide their decision-making processes with confidence. By leveraging our comprehensive data, clients can navigate the complexities of the NYC real estate market with greater ease and accuracy.

Apache Druid is a distributed data storage solution that is open source. Its fundamental architecture merges concepts from data warehouses, time series databases, and search technologies to deliver a high-performance analytics database capable of handling a diverse array of applications. By integrating the essential features from these three types of systems, Druid optimizes its ingestion process, storage method, querying capabilities, and overall structure. Each column is stored and compressed separately, allowing the system to access only the relevant columns for a specific query, which enhances speed for scans, rankings, and groupings. Additionally, Druid constructs inverted indexes for string data to facilitate rapid searching and filtering. It also includes pre-built connectors for various platforms such as Apache Kafka, HDFS, and AWS S3, as well as stream processors and others. The system adeptly partitions data over time, making queries based on time significantly quicker than those in conventional databases. Users can easily scale resources by simply adding or removing servers, and Druid will manage the rebalancing automatically. Furthermore, its fault-tolerant design ensures resilience by effectively navigating around any server malfunctions that may occur. This combination of features makes Druid a robust choice for organizations seeking efficient and reliable real-time data analytics solutions.

Digital badging can often present challenges, but Canvas Credentials simplifies the process significantly. By utilizing this innovative solution, you can expedite your objectives while ensuring that competencies are validated, engagement is fostered, completion rates are enhanced, and enrollment numbers rise. Not only does this approach boost student enrollment and retention, but it also provides a streamlined method for learners to document and share their verified skills and accomplishments with prospective employers. Canvas Credentials stands out as the premier open and inclusive digital credentialing network, dedicated to fostering a more equitable society through the recognition of verified skills and achievements. With Canvas Credentials, issuing badges that are rich in data, easy to share, and verifiable is a seamless experience, making it the sole open digital credentialing solution that offers visual and stackable learning pathways. Furthermore, it allows for the integration of credentials from various platforms, enabling learners to effectively curate and display their skills and accomplishments, while educators and employers can verify and utilize this skills data to achieve educational and workforce objectives, ultimately enhancing collaboration between all stakeholders in the learning ecosystem.

EMR serves as a comprehensive enterprise-grade big data platform, offering cluster, job, and data management functionalities that leverage various open-source technologies, including Hadoop, Spark, Kafka, Flink, and Storm. Alibaba Cloud Elastic MapReduce (EMR) is specifically designed for big data processing within the Alibaba Cloud ecosystem. Built on Alibaba Cloud's ECS instances, EMR integrates the capabilities of open-source Apache Hadoop and Apache Spark. This platform enables users to utilize components from the Hadoop and Spark ecosystems, such as Apache Hive, Apache Kafka, Flink, Druid, and TensorFlow, for effective data analysis and processing. Users can seamlessly process data stored across multiple Alibaba Cloud storage solutions, including Object Storage Service (OSS), Log Service (SLS), and Relational Database Service (RDS). EMR also simplifies cluster creation, allowing users to establish clusters rapidly without the hassle of hardware and software configuration. Additionally, all maintenance tasks can be managed efficiently through its user-friendly web interface, making it accessible for various users regardless of their technical expertise.

CelerData is an advanced SQL engine designed to enable high-performance analytics directly on data lakehouses, removing the necessity for conventional data warehouse ingestion processes. It achieves impressive query speeds in mere seconds, facilitates on-the-fly JOIN operations without incurring expensive denormalization, and streamlines system architecture by enabling users to execute intensive workloads on open format tables. Based on the open-source StarRocks engine, this platform surpasses older query engines like Trino, ClickHouse, and Apache Druid in terms of latency, concurrency, and cost efficiency. With its cloud-managed service operating within your own VPC, users maintain control over their infrastructure and data ownership while CelerData manages the upkeep and optimization tasks. This platform is poised to support real-time OLAP, business intelligence, and customer-facing analytics applications, and it has garnered the trust of major enterprise clients, such as Pinterest, Coinbase, and Fanatics, who have realized significant improvements in latency and cost savings. Beyond enhancing performance, CelerData’s capabilities allow businesses to harness their data more effectively, ensuring they remain competitive in a data-driven landscape.

BigLake serves as a storage engine that merges the functionalities of data warehouses and lakes, allowing BigQuery and open-source frameworks like Spark to efficiently access data while enforcing detailed access controls. It enhances query performance across various multi-cloud storage systems and supports open formats, including Apache Iceberg. Users can maintain a single version of data, ensuring consistent features across both data warehouses and lakes. With its capacity for fine-grained access management and comprehensive governance over distributed data, BigLake seamlessly integrates with open-source analytics tools and embraces open data formats. This solution empowers users to conduct analytics on distributed data, regardless of its storage location or method, while selecting the most suitable analytics tools, whether they be open-source or cloud-native, all based on a singular data copy. Additionally, it offers fine-grained access control for open-source engines such as Apache Spark, Presto, and Trino, along with formats like Parquet. As a result, users can execute high-performing queries on data lakes driven by BigQuery. Furthermore, BigLake collaborates with Dataplex, facilitating scalable management and logical organization of data assets. This integration not only enhances operational efficiency but also simplifies the complexities of data governance in large-scale environments.

Leisure Interactive stands as the pioneering force in the realm of outdoor hospitality, offering cutting-edge campground technology and marketing solutions, exemplified by their robust property management front office system, Hercules™. This innovative solution is equipped with an array of unique features that set it apart from competitors, such as the ability to cater to multiple business clients and processes through a single stackable online platform, real-time inventory management both online and offline, and a user-friendly web interface. Consequently, customers making reservations can now efficiently oversee one or several businesses through a single login while effortlessly managing the distribution of available inventory across various web portals and their own sites, enhancing the overall front office reservation process. Furthermore, Hercules™ not only simplifies management but also empowers businesses to optimize their operations and improve customer satisfaction.

The Korg KAOSSILATOR PRO+ is an innovative synthesizer and loop recorder that empowers musicians to craft and perform intricate music pieces across diverse genres through the intuitive X/Y touchpad interface. With a rich selection of 250 sound programs, which includes 62 fresh additions, it encompasses a wide range of styles such as hip-hop, house, dubstep, and rock. The device's loop recording feature allows for the capture of up to four measures, promoting an interactive performance experience with four infinitely stackable loop banks. Musicians can easily set specific musical scales and keys, ensuring their performances remain precise, and the built-in gate arpeggiator makes it simple to manipulate phrases using a slider. It is equipped with both line and mic inputs, enabling the recording of external audio sources, while its USB MIDI functionality allows it to serve as a flexible MIDI controller. Moreover, users can conveniently save loop data and external WAV files on SD/SDHC cards, and there is dedicated editor software available to manage sample data and settings effectively. This combination of features makes the KAOSSILATOR PRO+ a powerful tool for both live performance and studio recording.

Choose from our extensive library, adapt existing tools, or create your own features to effectively analyze and handle text, audio, and video content on a large scale. Seamlessly integrate sophisticated NLP functionalities into your applications or workflows. You can either utilize the resources available in the library or design personalized solutions. Effortlessly summarize, categorize, and examine language using modular and adaptable NLP components founded on cutting-edge models, all accessible through a single API request. Develop and refine tailored Language Skills with your own data utilizing our robust Custom-Skill engine. Considering that only 5% of the global population has English as their first language, it’s notable that most of One AI’s offerings support multiple languages. This means that whether you are creating a podcast platform, customer relationship management system, content publishing application, or any other type of product, you will have access to features such as language detection, processing, transcription, analytics, and comprehension capabilities, ensuring a versatile user experience across various languages. This flexibility empowers developers to cater to a wider audience and enhance user engagement.

Apache Spark™ serves as a comprehensive analytics platform designed for large-scale data processing. It delivers exceptional performance for both batch and streaming data by employing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and a robust execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, it supports interactive use through various shells including Scala, Python, R, and SQL. Spark supports a rich ecosystem of libraries such as SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming, allowing for seamless integration within a single application. It is compatible with various environments, including Hadoop, Apache Mesos, Kubernetes, and standalone setups, as well as cloud deployments. Furthermore, Spark can connect to a multitude of data sources, enabling access to data stored in systems like HDFS, Alluxio, Apache Cassandra, Apache HBase, and Apache Hive, among many others. This versatility makes Spark an invaluable tool for organizations looking to harness the power of large-scale data analytics.

Introducing a versatile, open-source multi-cloud platform for contemporary data applications, built on Apache Cassandra™. Achieve global-scale performance with guaranteed 100% uptime while avoiding vendor lock-in. You have the flexibility to deploy on multi-cloud environments, on-premises infrastructures, or use Kubernetes. The platform is designed to be elastic and offers a pay-as-you-go pricing model to enhance total cost of ownership. Accelerate your development process with Stargate APIs, which support NoSQL, real-time interactions, reactive programming, as well as JSON, REST, and GraphQL formats. Bypass the difficulties associated with managing numerous open-source projects and APIs that lack scalability. This solution is perfect for various sectors including e-commerce, mobile applications, AI/ML, IoT, microservices, social networking, gaming, and other highly interactive applications that require dynamic scaling based on demand. Start your journey of creating modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Leverage REST, GraphQL, and JSON alongside your preferred full-stack framework. This platform ensures that your richly interactive applications are not only elastic but also ready to gain traction from the very first day, all while offering a cost-effective Apache Cassandra DBaaS that scales seamlessly and affordably as your needs evolve. With this innovative approach, developers can focus on building rather than managing infrastructure.

A primary objective of Votrite is to foster a more inclusive and progressive atmosphere for individuals with disabilities, placing this ambition at the center of our technological innovations. Our solutions empower visually impaired voters to confidently participate in elections, ensuring their opinions are valued and acknowledged. Each Votrite EVS is designed to meet ADA standards, eliminating the need for any supplementary machines. Rather than maintaining large, outdated voting equipment, consider utilizing our compact, stackable all-in-one units. Alternatively, you can opt for Votrite's rental service, which frees you from the burden of storage entirely. Our systems also facilitate seamless integration with county and state voter-registration databases, ensuring accurate voter information. Additionally, we inform voters about their designated precincts and polling places while meticulously recording voting history and transmitting necessary data to state authorities. This comprehensive approach not only enhances accessibility but also streamlines the voting process for everyone involved.

Experience a comprehensive business solution that equips you with all the essential software tools required for robust deal flow, highlighted by a real estate wholesaling CRM complete with skip tracing capabilities. This package offers five outbound marketing channels, including SMS and email generation powered by ChatGPT, as well as additional marketing automation options like direct mail postcards and virtual phone systems for effective cold calling, alongside ringless voicemail features. Furthermore, it provides access to eight types of stackable motivated seller leads, inbound lead-generating websites, and data-driven deal analysis tools that include premium comparables and After Repair Value (ARV) assessments. REI/kit serves as a virtual real estate wholesaling software platform that is highly regarded by countless real estate investors, playing a crucial role in the expansion of their real estate investment operations. You can utilize our skip-traced motivated seller leads, which come with multiple contact points, or seamlessly import your own leads from preferred data sources. Enhance your outreach efforts by sending these leads targeted SmartText AI-generated SMS messages or emails, while automating the entire process for maximum efficiency. In addition, our platform's user-friendly interface ensures that even beginners can navigate and leverage these powerful tools effectively.

Experience Apache Kafka offered as a fully managed service that avoids vendor lock-in while providing comprehensive features for constructing your streaming pipeline. You can establish a fully managed Kafka instance in under 10 minutes using our intuitive web console or programmatically through our API, CLI, Terraform provider, or Kubernetes operator. Seamlessly integrate it with your current technology infrastructure using more than 30 available connectors, and rest assured with comprehensive logs and metrics that come standard through our service integrations. This fully managed distributed data streaming platform can be deployed in any cloud environment of your choice. It’s perfectly suited for applications that rely on event-driven architectures, facilitating near-real-time data transfers and pipelines, stream analytics, and any situation where swift data movement between applications is essential. With Aiven’s hosted and expertly managed Apache Kafka, you can effortlessly set up clusters, add new nodes, transition between cloud environments, and update existing versions with just a single click, all while keeping an eye on performance through a user-friendly dashboard. Additionally, this service enables businesses to scale their data solutions efficiently as their needs evolve.

MLlib, the machine learning library of Apache Spark, is designed to be highly scalable and integrates effortlessly with Spark's various APIs, accommodating programming languages such as Java, Scala, Python, and R. It provides an extensive range of algorithms and utilities, which encompass classification, regression, clustering, collaborative filtering, and the capabilities to build machine learning pipelines. By harnessing Spark's iterative computation features, MLlib achieves performance improvements that can be as much as 100 times faster than conventional MapReduce methods. Furthermore, it is built to function in a variety of environments, whether on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or within cloud infrastructures, while also being able to access multiple data sources, including HDFS, HBase, and local files. This versatility not only enhances its usability but also establishes MLlib as a powerful tool for executing scalable and efficient machine learning operations in the Apache Spark framework. The combination of speed, flexibility, and a rich set of features renders MLlib an essential resource for data scientists and engineers alike.

Vello is an exceptional platform for engaging with AI, offering rapid, robust, and collaborative multi-player AI chat that consolidates leading models and human partners in one accessible location. It is compatible across web, mobile, and desktop interfaces, providing a swift, keyboard-driven experience that enhances productivity. By integrating models from OpenAI, Anthropic, Google, Facebook, Cohere, and its proprietary web and document models, Vello facilitates immediate research with accurate source citations, effortless document composition, editing, and code refinement. The platform's team spaces foster collaboration between humans and AI, enabling users to work collaboratively in shared environments and chat rooms to complete tasks efficiently. Additionally, users have the ability to craft various AI personas, train them using diverse file types (including PDF, DOCX, code, CSV), and deploy them either individually or within multi-persona chat rooms, resulting in intricate workflows through round-robin model responses. This flexibility allows for a dynamic and highly customizable approach to utilizing AI technologies in a multitude of applications.

KPT is a toolchain focused on packages that offers a WYSIWYG configuration authoring, automation, and delivery experience, thereby streamlining the management of Kubernetes platforms and KRM-based infrastructure at scale by treating declarative configurations as independent data, distinct from the code that processes them. Many users of Kubernetes typically rely on traditional imperative graphical user interfaces, command-line utilities like kubectl, or automation methods such as operators that directly interact with Kubernetes APIs, while others opt for declarative configuration tools including Helm, Terraform, cdk8s, among numerous other options. At smaller scales, the choice of tools often comes down to personal preference and what users are accustomed to. However, as organizations grow the number of their Kubernetes development and production clusters, it becomes increasingly challenging to create and enforce uniform configurations and security policies across a wider environment, leading to potential inconsistencies. Consequently, KPT addresses these challenges by providing a more structured and efficient approach to managing configurations within Kubernetes ecosystems.

Amazon Managed Streaming for Apache Kafka (Amazon MSK) simplifies the process of creating and operating applications that leverage Apache Kafka for handling streaming data. As an open-source framework, Apache Kafka enables the construction of real-time data pipelines and applications. Utilizing Amazon MSK allows you to harness the native APIs of Apache Kafka for various tasks, such as populating data lakes, facilitating data exchange between databases, and fueling machine learning and analytical solutions. However, managing Apache Kafka clusters independently can be quite complex, requiring tasks like server provisioning, manual configuration, and handling server failures. Additionally, you must orchestrate updates and patches, design the cluster to ensure high availability, secure and durably store data, establish monitoring systems, and strategically plan for scaling to accommodate fluctuating workloads. By utilizing Amazon MSK, you can alleviate many of these burdens and focus more on developing your applications rather than managing the underlying infrastructure.

SiteWhere utilizes Kubernetes for deploying its infrastructure and microservices, making it versatile for both on-premise setups and virtually any cloud service provider. The system is supported by robust configurations of Apache Kafka, Zookeeper, and Hashicorp Consul, ensuring a reliable infrastructure. Each microservice is designed to scale individually while also enabling seamless integration with others. It presents a comprehensive multitenant IoT ecosystem that encompasses device management, event ingestion, extensive event storage capabilities, REST APIs, data integration, and additional features. The architecture is distributed and developed using Java microservices that operate on Docker, with an Apache Kafka processing pipeline for efficiency. Importantly, SiteWhere CE remains open source, allowing free use for both personal and commercial purposes. Additionally, the SiteWhere team provides free basic support along with a continuous flow of innovative features to enhance the platform's functionality. This emphasis on community-driven development ensures that users can benefit from ongoing improvements and updates.

Equalum offers a unique continuous data integration and streaming platform that seamlessly accommodates real-time, batch, and ETL scenarios within a single, cohesive interface that requires no coding at all. Transition to real-time capabilities with an intuitive, fully orchestrated drag-and-drop user interface designed for ease of use. Enjoy the benefits of swift deployment, powerful data transformations, and scalable streaming data pipelines, all achievable in just minutes. With a multi-modal and robust change data capture (CDC) system, it enables efficient real-time streaming and data replication across various sources. Its design is optimized for exceptional performance regardless of the data origin, providing the advantages of open-source big data frameworks without the usual complexities. By leveraging the scalability inherent in open-source data technologies like Apache Spark and Kafka, Equalum's platform engine significantly enhances the efficiency of both streaming and batch data operations. This cutting-edge infrastructure empowers organizations to handle larger data volumes while enhancing performance and reducing the impact on their systems, ultimately facilitating better decision-making and quicker insights. Embrace the future of data integration with a solution that not only meets current demands but also adapts to evolving data challenges.

BotKube is an innovative messaging bot designed for the monitoring and troubleshooting of Kubernetes clusters, developed and supported by InfraCloud. This versatile tool seamlessly integrates with various messaging platforms such as Slack, Mattermost, and Microsoft Teams, enabling users to oversee their Kubernetes environments, address critical deployment issues, and receive best practice recommendations through checks on Kubernetes resources. By observing Kubernetes activities, BotKube promptly alerts the designated channel about any noteworthy events, such as an ImagePullBackOff error, ensuring timely awareness. Users can tailor the specific objects and event severity levels they wish to monitor from their Kubernetes clusters, with the flexibility to enable or disable notifications as needed. Furthermore, BotKube is capable of executing kubectl commands within the Kubernetes cluster without requiring access to Kubeconfig or the underlying infrastructure, enhancing security. With BotKube, you can easily troubleshoot your deployments, services, or any other aspects of your cluster directly from your messaging interface, fostering a more efficient workflow. The ability to receive instant updates and perform actions from a familiar messaging platform significantly streamlines the management of Kubernetes environments.

Amazon EMR stands as the leading cloud-based big data solution for handling extensive datasets through popular open-source frameworks like Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. This platform enables you to conduct Petabyte-scale analyses at a cost that is less than half of traditional on-premises systems and delivers performance more than three times faster than typical Apache Spark operations. For short-duration tasks, you have the flexibility to quickly launch and terminate clusters, incurring charges only for the seconds the instances are active. In contrast, for extended workloads, you can establish highly available clusters that automatically adapt to fluctuating demand. Additionally, if you already utilize open-source technologies like Apache Spark and Apache Hive on-premises, you can seamlessly operate EMR clusters on AWS Outposts. Furthermore, you can leverage open-source machine learning libraries such as Apache Spark MLlib, TensorFlow, and Apache MXNet for data analysis. Integrating with Amazon SageMaker Studio allows for efficient large-scale model training, comprehensive analysis, and detailed reporting, enhancing your data processing capabilities even further. This robust infrastructure is ideal for organizations seeking to maximize efficiency while minimizing costs in their data operations.

While many Kubernetes platforms enable users to create and oversee Kubernetes clusters, Loft takes a different approach. Rather than being a standalone solution for managing clusters, Loft serves as an advanced control plane that enhances your current Kubernetes environments by introducing multi-tenancy and self-service functionalities, maximizing the benefits of Kubernetes beyond mere cluster oversight. It boasts an intuitive user interface and command-line interface, yet operates entirely on the Kubernetes framework, allowing seamless management through kubectl and the Kubernetes API, which ensures exceptional compatibility with pre-existing cloud-native tools. The commitment to developing open-source solutions is integral to our mission, as Loft Labs proudly holds membership with both the CNCF and the Linux Foundation. By utilizing Loft, organizations can enable their teams to create economical and efficient Kubernetes environments tailored for diverse applications, fostering innovation and agility in their workflows. This unique capability empowers businesses to harness the true potential of Kubernetes without the complexity often associated with cluster management.

Batch and streaming data processing can be streamlined effortlessly. With the capability to write once and run anywhere, it is ideal for mission-critical production tasks. Beam allows you to read data from a wide variety of sources, whether they are on-premises or cloud-based. It seamlessly executes your business logic across both batch and streaming scenarios. The outcomes of your data processing efforts can be written to the leading data sinks available in the market. This unified programming model simplifies operations for all members of your data and application teams. Apache Beam is designed for extensibility, with frameworks like TensorFlow Extended and Apache Hop leveraging its capabilities. You can run pipelines on various execution environments (runners), which provides flexibility and prevents vendor lock-in. The open and community-driven development model ensures that your applications can evolve and adapt to meet specific requirements. This adaptability makes Beam a powerful choice for organizations aiming to optimize their data processing strategies.

k0rdent is a Kubernetes-native platform engineering solution designed to unify and simplify distributed container infrastructure. Built as a fully open-source environment, it helps organizations manage multi-cluster and multi-cloud operations with consistency and control. By leveraging Kubernetes and Cluster API, k0rdent provides a portable and vendor-neutral foundation for modern application platforms. The platform allows teams to assemble custom developer platforms using validated, composable components and reusable templates. Declarative configuration and continuous reconciliation ensure clusters remain compliant and self-healing over time. k0rdent accelerates developer onboarding through self-service environments with minimal learning curves. It integrates seamlessly with GitOps and modern CI/CD pipelines to reduce manual operations. Unified observability improves insight into system health and resource usage. Policy-driven automation strengthens security and compliance across environments. k0rdent enables teams to scale infrastructure reliably while reducing cost and operational complexity.

OpenCost is an open-source initiative that is vendor-neutral, designed to measure and allocate costs associated with cloud infrastructure and containers in real-time. Developed by experts in Kubernetes and backed by practitioners in the field, OpenCost brings transparency to the often opaque spending patterns associated with Kubernetes. It offers flexible and customizable options for cost allocation and monitoring of cloud resources, facilitating accurate showback, chargeback, and continuous reporting. The tool provides real-time cost allocation that can be examined down to individual containers, ensuring precise tracking of expenses. It effectively allocates costs for in-cluster resources, including CPU, GPU, memory, load balancers, and persistent volumes. Additionally, OpenCost features dynamic asset pricing by integrating with billing APIs from AWS, Azure, and GCP, while also accommodating on-premises Kubernetes clusters with tailored pricing solutions. Beyond the Kubernetes cluster, it can monitor expenses from cloud providers related to resources such as object storage and databases, as well as other managed services. Furthermore, it seamlessly integrates with other open-source tools, allowing for convenient exports of pricing data to platforms like Prometheus, enhancing its utility in cost management. This makes OpenCost a comprehensive solution for organizations seeking to maintain control over their cloud spending effectively.

D2iQ Enterprise Kubernetes Platform (DKP) Enterprise Kubernetes Platform: Run Kubernetes Workloads at Scale D2iQ Kubernetes Platform (DKP): Adopt, expand, and enable advanced workloads across any infrastructure, whether on-prem, on the cloud, in air-gapped environments, or at the edge. Solve the Toughest Enterprise Kubernetes Challenges Accelerate the journey to production at scale, DKP provides a single, centralized point of control to build, run, and manage applications across any infrastructure. * Enable Day 2 Readiness Out-of-the-Box Without Lock-In * Simplify and Accelerate Kubernetes Adoption * Ensure Consistency, Security, and Performance * Expand Kubernetes Across Distributed Environments * Ensure Fast, Simple Deployment of ML and Fast Data Pipeline * Leverage Cloud Native Expertise

The Kubermatic Kubernetes Platform (KKP) facilitates digital transformation for enterprises by streamlining their cloud operations regardless of location. With KKP, operations and DevOps teams can easily oversee virtual machines and containerized workloads across diverse environments, including hybrid-cloud, multi-cloud, and edge, all through a user-friendly self-service portal designed for both developers and operations. As an open-source solution, KKP allows for the automation of thousands of Kubernetes clusters across various settings, ensuring unmatched density and resilience. It enables organizations to establish and run a multi-cloud self-service Kubernetes platform with minimal time to market, significantly enhancing efficiency. Developers and operations teams are empowered to deploy clusters in under three minutes on any infrastructure, which fosters rapid innovation. Workloads can be centrally managed from a single dashboard, providing a seamless experience whether in the cloud, on-premises, or at the edge. Furthermore, KKP supports the scalability of your cloud-native stack while maintaining enterprise-level governance, ensuring compliance and security throughout the infrastructure. This capability is essential for organizations aiming to maintain control and agility in today's fast-paced digital landscape.

We developed Conduktor, a comprehensive and user-friendly interface designed to engage with the Apache Kafka ecosystem seamlessly. Manage and develop Apache Kafka with assurance using Conduktor DevTools, your all-in-one desktop client tailored for Apache Kafka, which helps streamline workflows for your entire team. Learning and utilizing Apache Kafka can be quite challenging, but as enthusiasts of Kafka, we have crafted Conduktor to deliver an exceptional user experience that resonates with developers. Beyond merely providing an interface, Conduktor empowers you and your teams to take command of your entire data pipeline through our integrations with various technologies associated with Apache Kafka. With Conduktor, you gain access to the most complete toolkit available for working with Apache Kafka, ensuring that your data management processes are efficient and effective. This means you can focus more on innovation while we handle the complexities of your data workflows.

dstack simplifies GPU infrastructure management for machine learning teams by offering a single orchestration layer across multiple environments. Its declarative, container-native interface allows teams to manage clusters, development environments, and distributed tasks without deep DevOps expertise. The platform integrates natively with leading GPU cloud providers to provision and manage VM clusters while also supporting on-prem clusters through Kubernetes or SSH fleets. Developers can connect their desktop IDEs to powerful GPUs, enabling faster experimentation, debugging, and iteration. dstack ensures that scaling from single-instance workloads to multi-node distributed training is seamless, with efficient scheduling to maximize GPU utilization. For deployment, it supports secure, auto-scaling endpoints using custom code and Docker images, making model serving simple and flexible. Customers like Electronic Arts, Mobius Labs, and Argilla praise dstack for accelerating research while lowering costs and reducing infrastructure overhead. Whether for rapid prototyping or production workloads, dstack provides a unified, cost-efficient solution for AI development and deployment.

IBM Analytics for Apache Spark offers a versatile and cohesive Spark service that enables data scientists to tackle ambitious and complex inquiries while accelerating the achievement of business outcomes. This user-friendly, continually available managed service comes without long-term commitments or risks, allowing for immediate exploration. Enjoy the advantages of Apache Spark without vendor lock-in, supported by IBM's dedication to open-source technologies and extensive enterprise experience. With integrated Notebooks serving as a connector, the process of coding and analytics becomes more efficient, enabling you to focus more on delivering results and fostering innovation. Additionally, this managed Apache Spark service provides straightforward access to powerful machine learning libraries, alleviating the challenges, time investment, and risks traditionally associated with independently managing a Spark cluster. As a result, teams can prioritize their analytical goals and enhance their productivity significantly.

SelectDB is an innovative data warehouse built on Apache Doris, designed for swift query analysis on extensive real-time datasets. Transitioning from Clickhouse to Apache Doris facilitates the separation of the data lake and promotes an upgrade to a more efficient lake warehouse structure. This high-speed OLAP system handles nearly a billion query requests daily, catering to various data service needs across multiple scenarios. To address issues such as storage redundancy, resource contention, and the complexities of data governance and querying, the original lake warehouse architecture was restructured with Apache Doris. By leveraging Doris's capabilities for materialized view rewriting and automated services, it achieves both high-performance data querying and adaptable data governance strategies. The system allows for real-time data writing within seconds and enables the synchronization of streaming data from databases. With a storage engine that supports immediate updates and enhancements, it also facilitates real-time pre-polymerization of data for improved processing efficiency. This integration marks a significant advancement in the management and utilization of large-scale real-time data.

Samza enables the development of stateful applications that can handle real-time data processing from various origins, such as Apache Kafka. Proven to perform effectively at scale, it offers versatile deployment choices, allowing execution on YARN or as an independent library. With the capability to deliver remarkably low latencies and high throughput, Samza provides instantaneous data analysis. It can manage multiple terabytes of state through features like incremental checkpoints and host-affinity, ensuring efficient data handling. Additionally, Samza's operational simplicity is enhanced by its deployment flexibility—whether on YARN, Kubernetes, or in standalone mode. Users can leverage the same codebase to seamlessly process both batch and streaming data, which streamlines development efforts. Furthermore, Samza integrates with a wide range of data sources, including Kafka, HDFS, AWS Kinesis, Azure Event Hubs, key-value stores, and ElasticSearch, making it a highly adaptable tool for modern data processing needs.

Establish your Kubernetes infrastructure and utilize KubeGrid for the seamless deployment, monitoring, and optimization of potentially thousands of clusters. KubeGrid streamlines the complete lifecycle management of Kubernetes across both on-premises and cloud environments, allowing developers to effortlessly deploy, manage, and update numerous clusters. As a Platform as Code solution, KubeGrid enables you to declaratively specify all your Kubernetes needs in a code format, covering everything from your on-prem or cloud infrastructure to the specifics of clusters and autoscaling policies, with KubeGrid handling the deployment and management automatically. While most infrastructure-as-code solutions focus solely on provisioning, KubeGrid enhances the experience by automating Day 2 operations, including monitoring infrastructure, managing failovers for unhealthy nodes, and updating both clusters and their operating systems. Thanks to its innovative approach, Kubernetes excels in the automated provisioning of pods, ensuring efficient resource utilization across your infrastructure. By adopting KubeGrid, you transform the complexities of Kubernetes management into a streamlined and efficient process.

VeloDB, which utilizes Apache Doris, represents a cutting-edge data warehouse designed for rapid analytics on large-scale real-time data. It features both push-based micro-batch and pull-based streaming data ingestion that occurs in mere seconds, alongside a storage engine capable of real-time upserts, appends, and pre-aggregations. The platform delivers exceptional performance for real-time data serving and allows for dynamic interactive ad-hoc queries. VeloDB accommodates not only structured data but also semi-structured formats, supporting both real-time analytics and batch processing capabilities. Moreover, it functions as a federated query engine, enabling seamless access to external data lakes and databases in addition to internal data. The system is designed for distribution, ensuring linear scalability. Users can deploy it on-premises or as a cloud service, allowing for adaptable resource allocation based on workload demands, whether through separation or integration of storage and compute resources. Leveraging the strengths of open-source Apache Doris, VeloDB supports the MySQL protocol and various functions, allowing for straightforward integration with a wide range of data tools, ensuring flexibility and compatibility across different environments.

Apache Kylin™ is a distributed, open-source Analytical Data Warehouse designed for Big Data, aimed at delivering OLAP (Online Analytical Processing) capabilities in the modern big data landscape. By enhancing multi-dimensional cube technology and precalculation methods on platforms like Hadoop and Spark, Kylin maintains a consistent query performance, even as data volumes continue to expand. This innovation reduces query response times from several minutes to just milliseconds, effectively reintroducing online analytics into the realm of big data. Capable of processing over 10 billion rows in under a second, Kylin eliminates the delays previously associated with report generation, facilitating timely decision-making. It seamlessly integrates data stored on Hadoop with popular BI tools such as Tableau, PowerBI/Excel, MSTR, QlikSense, Hue, and SuperSet, significantly accelerating business intelligence operations on Hadoop. As a robust Analytical Data Warehouse, Kylin supports ANSI SQL queries on Hadoop/Spark and encompasses a wide array of ANSI SQL functions. Moreover, Kylin’s architecture allows it to handle thousands of simultaneous interactive queries with minimal resource usage, ensuring efficient analytics even under heavy loads. This efficiency positions Kylin as an essential tool for organizations seeking to leverage their data for strategic insights.

The engineering team at Altinity possesses extensive expertise, enabling them to implement a wide range of functionalities from essential ClickHouse features to the behavior of Kubernetes operators and enhancements for client libraries. They offer a versatile, docker-based GUI manager for ClickHouse that enables users to install clusters, manage nodes through addition, deletion, or replacement, monitor the status of clusters, and assist with troubleshooting and diagnostics. Additionally, they support various third-party tools and software integrations, including ingestion tools like Kafka and ClickTail, APIs for Python, Golang, ODBC, and Java, as well as compatibility with Kubernetes. UI tools such as Grafana, Superset, Tabix, and Graphite are also part of their ecosystem, along with database integrations for MySQL and PostgreSQL, and business intelligence tools like Tableau and many others. Altinity.Cloud draws upon its extensive experience gained from assisting numerous clients in managing ClickHouse-based analytics, ensuring it meets diverse needs. Built on a Kubernetes-based architecture, Altinity.Cloud offers both portability and flexibility regarding deployment options, allowing users to operate without fear of vendor lock-in. Recognizing that effective cost management is vital for SaaS companies, Altinity prioritizes this aspect in its offerings to support sustainable growth.

Crossplane is an open-source add-on for Kubernetes that allows platform teams to create infrastructure from various providers while offering higher-level self-service APIs for application teams to utilize, all without requiring any coding. You can provision and oversee cloud services and infrastructure using kubectl commands. By enhancing your Kubernetes cluster, Crossplane delivers Custom Resource Definitions (CRDs) for any infrastructure or managed service. These detailed resources can be combined into advanced abstractions that are easily versioned, managed, deployed, and utilized with your preferred tools and existing workflows already in place within your clusters. Crossplane was developed to empower organizations to construct their cloud environments similarly to how cloud providers develop theirs, utilizing a control plane approach. As a project under the Cloud Native Computing Foundation (CNCF), Crossplane broadens the Kubernetes API to facilitate the management and composition of infrastructure. Operators can define policies, permissions, and other protective measures through a custom API layer generated by Crossplane, ensuring that governance and compliance are maintained throughout the infrastructure lifecycle. This innovation paves the way for streamlined cloud management and enhances the overall developer experience.

Red Hat® OpenShift® Streams for Apache Kafka is a cloud-managed service designed to enhance the developer experience for creating, deploying, and scaling cloud-native applications, as well as for modernizing legacy systems. This service simplifies the processes of creating, discovering, and connecting to real-time data streams, regardless of their deployment location. Streams play a crucial role in the development of event-driven applications and data analytics solutions. By enabling seamless operations across distributed microservices and handling large data transfer volumes with ease, it allows teams to leverage their strengths, accelerate their time to value, and reduce operational expenses. Additionally, OpenShift Streams for Apache Kafka features a robust Kafka ecosystem and is part of a broader suite of cloud services within the Red Hat OpenShift product family, empowering users to develop a diverse array of data-driven applications. With its powerful capabilities, this service ultimately supports organizations in navigating the complexities of modern software development.

OpenFaaS® simplifies the deployment of serverless functions and existing applications onto Kubernetes, allowing users to utilize Docker to prevent vendor lock-in. This platform is versatile, enabling operation on any public or private cloud while supporting the development of microservices and functions in a variety of programming languages, including legacy code and binaries. It offers automatic scaling in response to demand or can scale down to zero when not in use. Users have the flexibility to work on their laptops, utilize on-premises hardware, or set up a cloud cluster. With Kubernetes handling the complexities, you can create a scalable and fault-tolerant, event-driven serverless architecture for your software projects. OpenFaaS allows you to start experimenting within just 60 seconds and to write and deploy your initial Python function in approximately 10 to 15 minutes. Following that, the OpenFaaS workshop provides a comprehensive series of self-paced labs that equip you with essential skills and knowledge about functions and their applications. Additionally, the platform fosters an ecosystem that encourages sharing, reusing, and collaborating on functions, while also minimizing boilerplate code through a template store that simplifies coding. This collaborative environment not only enhances productivity but also enriches the overall development experience.

Simplifying Multi-Cloud and Multi-Cluster Kubernetes application deployment and migration is now easier than ever with CAPE. Unlock the full potential of your Kubernetes capabilities with its key features, including Disaster Recovery that allows seamless backup and restore for stateful applications. With robust Data Mobility and Migration, you can securely manage and transfer applications and data across on-premises, private, and public cloud environments. CAPE also facilitates Multi-cluster Application Deployment, enabling stateful applications to be deployed efficiently across various clusters and clouds. Its intuitive Drag & Drop CI/CD Workflow Manager simplifies the configuration and deployment of complex CI/CD pipelines, making it accessible for users at all levels. The versatility of CAPE™ enhances Kubernetes operations by streamlining Disaster Recovery processes, facilitating Cluster Migration and Upgrades, ensuring Data Protection, enabling Data Cloning, and expediting Application Deployment. Moreover, CAPE provides a comprehensive control plane for federating clusters and managing applications and services seamlessly across diverse environments. This innovative tool brings clarity and efficiency to Kubernetes management, ensuring your applications thrive in a multi-cloud landscape.

GeoSpock revolutionizes data integration for a connected universe through its innovative GeoSpock DB, a cutting-edge space-time analytics database. This cloud-native solution is specifically designed for effective querying of real-world scenarios, enabling the combination of diverse Internet of Things (IoT) data sources to fully harness their potential, while also streamlining complexity and reducing expenses. With GeoSpock DB, users benefit from efficient data storage, seamless fusion, and quick programmatic access, allowing for the execution of ANSI SQL queries and the ability to link with analytics platforms through JDBC/ODBC connectors. Analysts can easily conduct evaluations and disseminate insights using familiar toolsets, with compatibility for popular business intelligence tools like Tableau™, Amazon QuickSight™, and Microsoft Power BI™, as well as support for data science and machine learning frameworks such as Python Notebooks and Apache Spark. Furthermore, the database can be effortlessly integrated with internal systems and web services, ensuring compatibility with open-source and visualization libraries, including Kepler and Cesium.js, thus expanding its versatility in various applications. This comprehensive approach empowers organizations to make data-driven decisions efficiently and effectively.

Achieve limitless data retention for Apache Kafka® with Confluent, empowering you to be infrastructure-enabled rather than constrained by outdated systems. Traditional technologies often force a choice between real-time processing and scalability, but event streaming allows you to harness both advantages simultaneously, paving the way for innovation and success. Have you ever considered how your rideshare application effortlessly analyzes vast datasets from various sources to provide real-time estimated arrival times? Or how your credit card provider monitors millions of transactions worldwide, promptly alerting users to potential fraud? The key to these capabilities lies in event streaming. Transition to microservices and facilitate your hybrid approach with a reliable connection to the cloud. Eliminate silos to ensure compliance and enjoy continuous, real-time event delivery. The possibilities truly are limitless, and the potential for growth is unprecedented.