Business Software for Apache Kafka

We make BI and Big Data analytics easier and more efficient. Our goal is to empower business users, make BI specialists and always-busy business more independent when solving data-driven business problems. Querona is a solution for those who have ever been frustrated by a lack in data, slow or tedious report generation, or a long queue to their BI specialist. Querona has a built-in Big Data engine that can handle increasing data volumes. Repeatable queries can be stored and calculated in advance. Querona automatically suggests improvements to queries, making optimization easier. Querona empowers data scientists and business analysts by giving them self-service. They can quickly create and prototype data models, add data sources, optimize queries, and dig into raw data. It is possible to use less IT. Users can now access live data regardless of where it is stored. Querona can cache data if databases are too busy to query live.

Ataccama is a revolutionary way to manage data and create enterprise value. Ataccama unifies Data Governance, Data Quality and Master Data Management into one AI-powered fabric that can be used in hybrid and cloud environments. This gives your business and data teams unprecedented speed and security while ensuring trust, security and governance of your data.

Utilihive, a cloud-native big-data integration platform, is offered as a managed (SaaS) service. Utilihive, the most popular Enterprise-iPaaS (iPaaS), is specifically designed for utility and energy usage scenarios. Utilihive offers both the technical infrastructure platform (connectivity and integration, data ingestion and data lake management) and preconfigured integration content or accelerators. (connectors and data flows, orchestrations and utility data model, energy services, monitoring and reporting dashboards). This allows for faster delivery of data-driven services and simplifies operations.

ScyllaDB serves as an ideal database solution for applications that demand high performance and minimal latency, catering specifically to data-intensive needs. It empowers teams to fully utilize the growing computing capabilities of modern infrastructures, effectively removing obstacles to scaling as data volumes expand. Distinct from other database systems, ScyllaDB stands out as a distributed NoSQL database that is completely compatible with both Apache Cassandra and Amazon DynamoDB, while incorporating significant architectural innovations that deliver outstanding user experiences at significantly reduced costs. Over 400 transformative companies, including Disney+ Hotstar, Expedia, FireEye, Discord, Zillow, Starbucks, Comcast, and Samsung, rely on ScyllaDB to tackle their most challenging database requirements. Furthermore, ScyllaDB is offered in various formats, including a free open-source version, a fully-supported enterprise solution, and a fully managed database-as-a-service (DBaaS) available across multiple cloud platforms, ensuring flexibility for diverse user needs. This versatility makes it an attractive choice for organizations looking to optimize their database performance.

Red Hat AMQ serves as a versatile messaging platform that ensures reliable information delivery, fostering real-time integration and enabling connectivity for the Internet of Things (IoT). Built on the foundations of open source projects such as Apache ActiveMQ and Apache Kafka, it accommodates a range of messaging patterns, allowing for the swift and effective integration of applications, endpoints, and devices, which ultimately boosts enterprise agility and responsiveness. With the ability to facilitate high-throughput and low-latency data sharing among microservices and other applications, AMQ significantly enhances operational efficiency. Furthermore, it offers connectivity options for client programs developed in various programming languages, ensuring broad compatibility. The platform also establishes an open-wire protocol for messaging interoperability, which permits businesses to implement diverse distributed messaging solutions tailored to their changing needs. Supported by the award-winning services of Red Hat, AMQ is recognized for its ability to underpin mission-critical applications, reinforcing its value in enterprise environments. Additionally, its adaptability makes it an ideal choice for organizations aiming to stay ahead in a rapidly evolving digital landscape.

In the field of IoT stream processing and analytics, SQLstream ranks #1 according to ABI Research. Used by Verizon, Walmart, Cisco, and Amazon, our technology powers applications on premises, in the cloud, and at the edge. SQLstream enables time-critical alerts, live dashboards, and real-time action with sub-millisecond latency. Smart cities can reroute ambulances and fire trucks or optimize traffic light timing based on real-time conditions. Security systems can detect hackers and fraudsters, shutting them down right away. AI / ML models, trained with streaming sensor data, can predict equipment failures. Thanks to SQLstream's lightning performance -- up to 13 million rows / second / CPU core -- companies have drastically reduced their footprint and cost. Our efficient, in-memory processing allows operations at the edge that would otherwise be impossible. Acquire, prepare, analyze, and act on data in any format from any source. Create pipelines in minutes not months with StreamLab, our interactive, low-code, GUI dev environment. Edit scripts instantly and view instantaneous results without compiling. Deploy with native Kubernetes support. Easy installation includes Docker, AWS, Azure, Linux, VMWare, and more

TENGU is a Data orchestration platform that serves as a central workspace for all data profiles to work more efficiently and enhance collaboration. Allowing you to get the most out of your data, faster. It allows complete control over your data environment in an innovative graph view for intuitive monitoring. Connecting all necessary tools in one workspace. It enables self-service, monitoring and automation, supporting all data roles and operations from integration to transformation.

StackStorm seamlessly integrates your applications, services, and workflows into a cohesive system. Whether you're implementing straightforward if/then rules or designing intricate workflows, StackStorm empowers you to tailor your DevOps automation to meet your specific needs. There's no requirement to alter your current processes, as StackStorm works with the tools you already utilize. The strength of a product is often amplified by its community, and StackStorm boasts a vibrant user base worldwide, ensuring you always have access to support and resources. This platform is capable of automating and optimizing almost every aspect of your organization, with several popular use cases. In instances of system failures, StackStorm can serve as your initial support tier, diagnosing issues, resolving known errors, and escalating to human intervention when necessary. Managing continuous deployment can become increasingly intricate, surpassing what Jenkins or other specialized tools offer, but StackStorm allows you to automate sophisticated CI/CD pipelines according to your preferences. Additionally, ChatOps merges automation with teamwork, enhancing the productivity and efficiency of DevOps teams while adding a touch of style to their workflow. Ultimately, StackStorm is designed to evolve with your organization’s needs, fostering innovation and efficiency at every turn.

Platform engineering is revolutionizing how engineering organizations build and run their cloud-native setups. Humanitec is leading this revolution, providing enteprises with the fastest and most reliable way to build Internal Developer Platforms (IDPs). Humanitec is the leader in the platform engineering space. Named a 2022 Gartner® Cool Vendor, we drive developer productivity by radically simplifying how teams deliver software at scale. Our core product, the Humanitec Platform Orchestrator, is used by mid and large-size engineering organizations, from 100+ developer scale-ups all the way to Fortune 100s. Our OSS workload specification Score lets developers describe their workloads and dependencies as code. The Platform Orchestrator dynamically generates app and infra configurations with every new deployment, driving standardization across the entire software delivery lifecycle. This means no more ticket ops or waiting times for developers, resulting in 4x higher deployment frequency and 30% faster time to market. As a SaaS provider, Humanitec takes information security very seriously. We’re ISO 27001 certified and constantly strive to protect data while adhering to the industry’s best security practices.

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.

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.

Empower individuals to explore and analyze streaming data effectively. By sharing, documenting, and organizing your data, you can boost productivity by as much as 95%. Once you have your data, you can create applications tailored for real-world use cases. Implement a security model focused on data to address the vulnerabilities associated with open source technologies, ensuring data privacy is prioritized. Additionally, offer secure and low-code data pipeline functionalities that enhance usability. Illuminate all hidden aspects and provide unmatched visibility into data and applications. Integrate your data mesh and technological assets, ensuring you can confidently utilize open-source solutions in production environments. Lenses has been recognized as the premier product for real-time stream analytics, based on independent third-party evaluations. With insights gathered from our community and countless hours of engineering, we have developed features that allow you to concentrate on what generates value from your real-time data. Moreover, you can deploy and operate SQL-based real-time applications seamlessly over any Kafka Connect or Kubernetes infrastructure, including AWS EKS, making it easier than ever to harness the power of your data. By doing so, you will not only streamline operations but also unlock new opportunities for innovation.

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.

Apache Ranger™ serves as a framework designed to facilitate, oversee, and manage extensive data security within the Hadoop ecosystem. The goal of Ranger is to implement a thorough security solution throughout the Apache Hadoop landscape. With the introduction of Apache YARN, the Hadoop platform can effectively accommodate a genuine data lake architecture, allowing businesses to operate various workloads in a multi-tenant setting. As the need for data security in Hadoop evolves, it must adapt to cater to diverse use cases regarding data access, while also offering a centralized framework for the administration of security policies and the oversight of user access. This centralized security management allows for the execution of all security-related tasks via a unified user interface or through REST APIs. Additionally, Ranger provides fine-grained authorization, enabling specific actions or operations with any Hadoop component or tool managed through a central administration tool. It standardizes authorization methods across all Hadoop components and enhances support for various authorization strategies, including role-based access control, thereby ensuring a robust security framework. By doing so, it significantly strengthens the overall security posture of organizations leveraging Hadoop technologies.

Achieve rapid automation for your data warehouse with Vaultspeed, an innovative tool adhering to the Data Vault 2.0 standards and backed by a decade of practical experience in data integration. This solution supports a comprehensive range of Data Vault 2.0 objects and offers various implementation options. It enables the swift generation of high-quality code across all scenarios within a Data Vault 2.0 integration framework. By integrating Vaultspeed into your existing setup, you can maximize your investments in both tools and expertise. You will also enjoy guaranteed compliance with the most recent Data Vault 2.0 standard, thanks to our ongoing collaboration with Scalefree, the authoritative knowledge source for the Data Vault 2.0 community. The Data Vault 2.0 modeling methodology simplifies model components to their essential elements, facilitating a uniform loading pattern and consistent database structure. Furthermore, Vaultspeed utilizes a template system that comprehensively understands the various object types and includes straightforward configuration settings, enhancing user experience and efficiency in data management.

Macaw serves as an advanced enterprise platform specifically designed to create and enhance applications suited for the digital era. It introduces a distinctive method for upgrading legacy applications, enabling them to leverage containerization and microservices technologies effectively. Additionally, Macaw presents a comprehensive solution that aids enterprises in the design, development, publication, execution, and management of microservices-based applications, all while remaining agnostic to the underlying infrastructure and cloud environments. This platform is ideal for organizations eager to expedite their modernization efforts through a hybrid-cloud approach and the adoption of cloud-native applications. With its array of integrated foundational services, operational features, and seamless Kubernetes integration, Macaw equips users with the essential runtime environment, tools, and services necessary for building, deploying, and overseeing microservices applications. Furthermore, it boasts a variety of core application services that are readily available, including database management, security protocols, messaging systems, and load balancing, facilitating quicker development cycles and streamlined operations. Ultimately, Macaw stands out as a versatile solution for enterprises aiming to thrive in a rapidly evolving technological landscape.

Y42 is the first fully managed Modern DataOps Cloud for production-ready data pipelines on top of Google BigQuery and Snowflake.

Actian Data Platform is an integrated data management solution designed to handle data integration, warehousing, and analytics in a single environment. It enables organizations to connect, manage, and analyze data across hybrid infrastructures, including on-premises and cloud systems. The platform offers over 200 pre-built connectors and APIs to automate data pipelines and reduce engineering effort. It supports real-time analytics, allowing users to work with up-to-date data for faster insights. Advanced columnar storage and vectorized processing ensure high performance and scalability for large datasets. The platform includes built-in data quality tools that help maintain accuracy and consistency across data workflows. Actian Data Platform also supports high concurrency, enabling multiple users and processes to run simultaneously without performance issues. It provides flexible deployment options, including public cloud, multi-cloud, and hybrid environments. The system simplifies analytics and reporting by integrating with popular business intelligence tools. It is designed to reduce costs while improving performance compared to traditional data platforms. By combining integration, storage, and analytics, Actian Data Platform helps organizations streamline their data operations.

Using OpenEBS in conjunction with Kubera is the optimal solution for storage needs in Kubernetes environments. OpenEBS stands out as the leading open source storage option for Kubernetes, recognized for its speed and efficiency. Kubera enhances OpenEBS Mayastor by providing a user-friendly graphical interface, along with APIs, automatic checks, configuration options, Active Directory authentication, built-in performance benchmarks, and additional operators to streamline upgrades and various other scenarios. Available at no cost, Kubera is offered by MayaData, which also provides round-the-clock support to help customers minimize operational expenses and simplify management. Kubera Propel, a cloud-native declarative data plane crafted in Rust, is built upon the foundational OpenEBS Mayastor technology. This innovative platform integrates cutting-edge technologies such as NVMe, SPDK, and new storage capabilities emerging within the Linux kernel. Independent benchmarks have demonstrated that OpenEBS, when governed by Kubera Propel, achieves remarkably low latency performance for databases and various workloads on Kubernetes, making it an excellent choice for developers and organizations alike. This combination not only enhances performance but also addresses the increasing demand for efficient and reliable storage solutions in modern computing environments.

Reduce your cloud expenses, enhance security, and boost developer efficiency. Why waste funds on cloud providers? Our solution allows you to monitor your expenditures and implement straightforward, machine learning-driven strategies to cut costs. Explore our assortment of over 60 applications available in the AWS Marketplace, designed for easy deployment at the most competitive prices. Safeguard your cloud infrastructure and efficiently manage EC2 instance updates across various regions through a unified interface. Our intuitive dashboard enables you to analyze and optimize your AWS spending thoroughly. It automatically identifies and eliminates unused AWS resources to help lower costs. Benefit from ongoing machine learning assessments to continually minimize cloud expenses. Instead of focusing on building complex application stacks, utilize our pre-configured, secure images available right off the shelf. This way, you can focus more on coding rather than getting caught up in operations. Additionally, our solution scans your AWS environment for security vulnerabilities, providing assistance in mitigating risks. With the capability to patch servers across multiple regions from one centralized dashboard, managing your cloud infrastructure has never been easier.

StackPulse streamlines and enhances the processes of incident response and management, fostering a seamless commitment to the reliability of software services. It equips Site Reliability Engineers, developers, and on-call personnel with the essential context and authority to effectively analyze, address, and resolve incidents throughout the entire stack, regardless of scale. By revolutionizing how engineering and operations teams handle software and infrastructure services, StackPulse introduces a collaborative platform filled with various incident management tools. Users can effortlessly initiate teamwork through automated war room setups, efficient data collection, and auto-generated postmortem reports. The insights gathered during incidents pave the way for tailored recommendations on playbooks and triggers, leading to remarkable decreases in Mean Time to Recovery (MTTR) and enhanced adherence to Service Level Objectives (SLOs). Additionally, StackPulse identifies risks by analyzing unique patterns within an organization’s monitoring, infrastructure, and operational data, offering customized automated playbooks that suit specific organizational needs. This approach not only mitigates risks but also empowers teams to better manage their operational challenges.

It is commonly believed that containers are primarily suited for stateless applications. Nevertheless, numerous organizations are recognizing the benefits of containerizing their databases for similar reasons as those for their web applications, including the ability to deploy updates more frequently, the simplicity of transitioning from development to staging to production, and the versatility to operate the same workload across various infrastructures. A recent survey by Diamanti has even identified databases as a leading use case for container adoption. Cloud Native infrastructure provides the capability for stateful applications to leverage elasticity and flexibility efficiently. Despite this, events such as hardware malfunctions, power outages, natural disasters, or other unforeseen circumstances can lead to significant data loss. This scenario complicates the recovery process for stateful applications, making it a critical challenge. Consequently, one of the key requirements for cloud native storage solutions is to ensure seamless recovery from such catastrophic incidents, enabling organizations to maintain data integrity and availability. Ultimately, as organizations continue to embrace containerization, addressing these challenges will be essential for maximizing the benefits of their deployments.

If you're looking to establish a governed delta lake, create a data warehouse, or transition from a conventional database to a contemporary cloud data solution, Lyftrondata has you covered. You can effortlessly create and oversee all your data workloads within a single platform, automating the construction of your pipeline and warehouse. Instantly analyze your data using ANSI SQL and business intelligence or machine learning tools, and easily share your findings without the need for custom coding. This functionality enhances the efficiency of your data teams and accelerates the realization of value. You can define, categorize, and locate all data sets in one centralized location, enabling seamless sharing with peers without the complexity of coding, thus fostering insightful data-driven decisions. This capability is particularly advantageous for organizations wishing to store their data once, share it with various experts, and leverage it repeatedly for both current and future needs. In addition, you can define datasets, execute SQL transformations, or migrate your existing SQL data processing workflows to any cloud data warehouse of your choice, ensuring flexibility and scalability in your data management strategy.

The enterprise database for time series, documents, and vectors. Store any type data and combine the simplicity and scalability NoSQL with SQL. CrateDB is a distributed database that runs queries in milliseconds regardless of the complexity, volume, and velocity.

Mule serves as the runtime engine for the Anypoint Platform, functioning as a nimble Java-based enterprise service bus (ESB) and integration platform that simplifies the process for developers to link applications efficiently, facilitating data exchange. This platform promotes seamless integration of diverse systems, irrespective of the various technologies involved, such as JMS, Web Services, JDBC, and HTTP, among others. Capable of being deployed in multiple environments, the ESB can manage and orchestrate events either in real time or in batch processes while offering universal connectivity. A significant benefit of utilizing an ESB is its ability to enable communication between disparate applications, functioning as a transit system that carries data across different applications within an organization or over the Internet. Furthermore, it allows for the exposure and hosting of reusable services by utilizing the ESB as a lightweight service container, while also providing a shield against various message formats and protocols. By decoupling business logic from messaging, the ESB empowers location-independent service calls, enhancing the flexibility and scalability of integration solutions. Overall, Mule enhances the capability of organizations to create a more interconnected digital ecosystem.