Alternatives to Red Hat OpenShift Streams

Cloud-based solution for observability that helps businesses manage and track workload and performance through a single dashboard. Monitor all the services you run on your cloud without compromising cost, granularity or scale. Groundcover is a cloud-native APM solution that makes observability easy so you can focus on creating world-class products. Groundcover's proprietary sensor unlocks unprecedented granularity for all your applications. This eliminates the need for costly changes in code and development cycles, ensuring monitoring continuity.

Kubernetes is the platform for big ideas. The leading enterprise container platform, hybrid cloud, empowers developers to innovate faster and ship more products. Red Hat OpenShift automates installation, upgrades, lifecycle management, and lifecycle management for the entire container stack, including Kubernetes, cluster services, and applications. It can be used on any cloud. Red Hat OpenShift allows teams to build with speed, agility and confidence. You can code in production mode wherever you choose to build. Do the important work. Red Hat OpenShift focuses on security at all levels of the container stack as well as throughout the application lifecycle. It includes enterprise support from one the most prominent Kubernetes contributors as well as open source software companies.

Data integration for hybrid clouds Modern, reliable data integration across both your private cloud and public cloud. All this in real-time, with change data capture and streams. Striim was developed by the executive and technical team at GoldenGate Software. They have decades of experience in mission critical enterprise workloads. Striim can be deployed in your environment as a distributed platform or in the cloud. Your team can easily adjust the scaleability of Striim. Striim is fully secured with HIPAA compliance and GDPR compliance. Built from the ground up to support modern enterprise workloads, whether they are hosted in the cloud or on-premise. Drag and drop to create data flows among your sources and targets. Real-time SQL queries allow you to process, enrich, and analyze streaming data.

IBM Event Streams leverages Apache Kafka to provide high-performance event streaming solutions for businesses. The platform offers seamless integrations, scalability, and real-time processing for applications, allowing enterprises to make data-driven decisions faster. IBM's service ensures durability, high availability, and secure handling of event data across cloud environments. With tools like schema registry and Kafka Connect, Event Streams supports robust event-driven architectures, helping businesses streamline workflows, increase responsiveness, and enhance customer experience.

Apache Kafka can be utilized as a comprehensive managed service that ensures no vendor lock-in and provides all the necessary features to construct your streaming pipeline effectively. You can establish fully managed Kafka in under ten minutes using our web interface or programmatically through various methods such as our API, CLI, Terraform provider, or Kubernetes operator. Seamlessly integrate it with your current technology stack using more than 30 connectors, while maintaining peace of mind with logs and metrics readily available through the service integrations. This fully managed distributed data streaming platform is available for deployment in the cloud environment of your choice. It is particularly suited for event-driven applications, near-real-time data transfers, and data pipelines, as well as stream analytics and any scenario requiring rapid data movement between applications. With Aiven's hosted and fully managed Apache Kafka, you can easily set up clusters, deploy new nodes, migrate between clouds, and upgrade existing versions with just a click, all while being able to monitor everything effortlessly through an intuitive dashboard. This convenience and efficiency make it an excellent choice for developers and organizations looking to optimize their data streaming capabilities.

Engaging applications captivate users while motivating developers to innovate. To meet the growing demands of the digital landscape, consider utilizing the DataStax Astra Streaming service platform. This cloud-native platform for messaging and event streaming is built on the robust foundation of Apache Pulsar. With Astra Streaming, developers can create streaming applications that leverage a multi-cloud, elastically scalable architecture. Powered by the advanced capabilities of Apache Pulsar, this platform offers a comprehensive solution that encompasses streaming, queuing, pub/sub, and stream processing. Astra Streaming serves as an ideal partner for Astra DB, enabling current users to construct real-time data pipelines seamlessly connected to their Astra DB instances. Additionally, the platform's flexibility allows for deployment across major public cloud providers, including AWS, GCP, and Azure, thereby preventing vendor lock-in. Ultimately, Astra Streaming empowers developers to harness the full potential of their data in real-time environments.

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.

WarpStream, an Apache Kafka compatible data streaming platform, is built directly on object storage. It has no inter-AZ network costs, no disks that need to be managed, and it's infinitely scalable within your VPC. WarpStream is deployed in your VPC as a stateless, auto-scaling binary agent. No local disks are required to be managed. Agents stream data directly into and out of object storage without buffering on local drives and no data tiering. Instantly create new "virtual" clusters in our control plan. Support multiple environments, teams or projects without having to manage any dedicated infrastructure. WarpStream is Apache Kafka protocol compatible, so you can continue to use your favorite tools and applications. No need to rewrite or use a proprietary SDK. Simply change the URL of your favorite Kafka library in order to start streaming. Never again will you have to choose between budget and reliability.

Streaming service is a streaming service that allows developers and data scientists to stream real-time events. It is serverless and Apache Kafka compatible. Streaming can be integrated with Oracle Cloud Infrastructure, Database, GoldenGate, Integration Cloud, and Oracle Cloud Infrastructure (OCI). The service provides integrations for hundreds third-party products, including databases, big data, DevOps, and SaaS applications. Data engineers can easily create and manage big data pipelines. Oracle manages all infrastructure and platform management, including provisioning, scaling and security patching. Streaming can provide state management to thousands of consumers with the help of consumer groups. This allows developers to easily create applications on a large scale.

Axual serves as a Kafka-as-a-Service tailored for DevOps teams, empowering them to gain insights and make informed decisions through our user-friendly Kafka platform. For enterprises aiming to effortlessly incorporate data streaming into their foundational IT systems, Axual presents the ultimate solution. Our comprehensive Kafka platform is crafted to remove the necessity for in-depth technical expertise, offering an out-of-the-box solution that provides all the advantages of event streaming without the complications that typically accompany it. The Axual Platform stands as a complete solution, specifically designed to streamline and improve the deployment, management, and application of real-time data streaming using Apache Kafka. By offering a diverse range of features that address the varying requirements of contemporary enterprises, the Axual Platform allows organizations to fully leverage the capabilities of data streaming while significantly reducing complexity and operational burdens. This innovative approach not only simplifies processes but also empowers teams to focus on strategic initiatives.

Professional applications can be built to automate workflows, monitor operations continuously, and control processes in real time. Your solutions can run 24/7 on servers at the edge and in the cloud. The spreadsheet user interface makes it easy to create software without being a programmer. Instead of writing program code you can drag-and-drop data and fill cells with formulas to create charts in a way that you already know. You will find all the protocols you need to connect sensors and machines such as MQTT, OPC UA, and REST on board. Streamsheets is a native stream data processing tool like MQTT or kafka. You can grab a topic stream and transform it to broadcast it out into the endless streaming universe. REST gives you access to the world. Streamsheets allow you to connect to any web service, or let them connect to your site. Streamsheets can be run on your servers in the cloud, on your edge devices, or on your Raspberry Pi.

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.

The Open, Multi-Cloud Stack to Modern Data Apps. Built on Apache Cassandra™, an open-source Apache Cassandra™. Global scale and 100% uptime without vendor lock in You can deploy on multi-clouds, open-source, on-prem and Kubernetes. For a lower TCO, use elastic and pay-as you-go. Stargate APIs allow you to build faster with NoSQL, reactive, JSON and REST. Avoid the complexity of multiple OSS projects or APIs that don’t scale. It is ideal for commerce, mobile and AI/ML. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Richly interactive apps that are viral-ready and elastic using REST, GraphQL and JSON. Pay-as you-go Apache Cassandra DBaaS which scales easily and affordably

Solace is a specialist in Event-Driven-Architecture (EDA), with two decades of experience providing enterprises with highly reliable, robust and scalable data movement technology based on the publish & subscribe (pub/sub) pattern. Solace technology enables the real-time data flow behind many of the conveniences you take for granted every day such as immediate loyalty rewards from your credit card, the weather data delivered to your mobile phone, real-time airplane movements on the ground and in the air, and timely inventory updates to some of your favourite department stores and grocery chains, not to mention that Solace technology also powers many of the world's leading stock exchanges and betting houses. Aside from rock solid technology, stellar customer support is one of the biggest reasons customers select Solace, and stick with them.

DeltaStream is an integrated serverless streaming processing platform that integrates seamlessly with streaming storage services. Imagine it as a compute layer on top your streaming storage. It offers streaming databases and streaming analytics along with other features to provide an integrated platform for managing, processing, securing and sharing streaming data. DeltaStream has a SQL-based interface that allows you to easily create stream processing apps such as streaming pipelines. It uses Apache Flink, a pluggable stream processing engine. DeltaStream is much more than a query-processing layer on top Kafka or Kinesis. It brings relational databases concepts to the world of data streaming, including namespacing, role-based access control, and enables you to securely access and process your streaming data, regardless of where it is stored.

Event Hubs serves as a fully managed service for real-time data ingestion, offering simplicity, reliability, and scalability. It enables the streaming of millions of events per second from diverse sources, facilitating the creation of dynamic data pipelines that allow for immediate responses to business obstacles. In times of emergencies, you can continue processing data thanks to its geo-disaster recovery and geo-replication capabilities. The service integrates effortlessly with other Azure offerings, unlocking valuable insights. Additionally, existing Apache Kafka clients and applications can connect to Event Hubs without the need for code modifications, providing a managed Kafka experience without the burden of handling your own clusters. You can enjoy both real-time data ingestion and microbatching within the same stream, allowing you to concentrate on extracting insights from your data rather than managing infrastructure. With Event Hubs, you can construct real-time big data pipelines and swiftly tackle business challenges as they arise, ensuring your organization remains agile and responsive in a fast-paced environment.

Allow everyone to view and discover streaming data. Up to 95% of productivity can be increased by sharing, documenting, and cataloging data. Next, create apps for production use cases using the data. To address privacy concerns and cover all the gaps in open source technology, apply a data-centric security approach. Secure and low-code data pipeline capabilities. All darkness is eliminated and data and apps can be viewed with unparalleled visibility. Unify your data technologies and data meshes and feel confident using open source production. Independent third-party reviews have rated Lenses the best product for real time stream analytics. We have built features to allow you to focus on what is driving value from real-time data. This was based on feedback from our community as well as thousands of engineering hours. You can deploy and run SQL-based real-time applications over any Kafka Connect, Kubernetes or Kubernetes infrastructure, including AWS EKS.

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.

Unified stream and batch data processing that is serverless, fast, cost-effective, and low-cost. Fully managed data processing service. Automated provisioning of and management of processing resource. Horizontal autoscaling worker resources to maximize resource use Apache Beam SDK is an open-source platform for community-driven innovation. Reliable, consistent processing that works exactly once. Streaming data analytics at lightning speed Dataflow allows for faster, simpler streaming data pipeline development and lower data latency. Dataflow's serverless approach eliminates the operational overhead associated with data engineering workloads. Dataflow allows teams to concentrate on programming and not managing server clusters. Dataflow's serverless approach eliminates operational overhead from data engineering workloads, allowing teams to concentrate on programming and not managing server clusters. Dataflow automates provisioning, management, and utilization of processing resources to minimize latency.

Scale from zero to millions of events every second with Arroyo, which is delivered as a single, streamlined binary. It can be run locally on either MacOS or Linux for development purposes and easily deployed to production using Docker or Kubernetes. Arroyo represents a revolutionary approach to stream processing, specifically designed to simplify real-time operations compared to traditional batch processing. From its inception, Arroyo has been crafted so that anyone familiar with SQL can create dependable, efficient, and accurate streaming pipelines. This empowers data scientists and engineers to develop comprehensive real-time applications, models, and dashboards without needing a dedicated team of streaming specialists. Users can perform transformations, filtering, aggregation, and joining of data streams simply by writing SQL, achieving results in under a second. Furthermore, your streaming pipelines shouldn’t trigger alerts just because Kubernetes opted to reschedule your pods. With the capability to operate in contemporary, elastic cloud environments, Arroyo is suitable for everything from basic container runtimes like Fargate to extensive, distributed systems managed by Kubernetes. This versatility makes Arroyo an ideal choice for organizations looking to optimize their streaming data processes.

Apache Kafka® is a robust, open-source platform designed for distributed streaming. It allows for the scaling of production clusters to accommodate up to a thousand brokers, handling trillions of messages daily and managing petabytes of data across hundreds of thousands of partitions. The system provides the flexibility to seamlessly expand or reduce storage and processing capabilities. It can efficiently stretch clusters over various availability zones or link distinct clusters across different geographical regions. Users can process streams of events through a variety of operations such as joins, aggregations, filters, and transformations, with support for event-time and exactly-once processing guarantees. Kafka features a Connect interface that readily integrates with numerous event sources and sinks, including technologies like Postgres, JMS, Elasticsearch, and AWS S3, among many others. Additionally, it supports reading, writing, and processing event streams using a wide range of programming languages, making it accessible for diverse development needs. This versatility and scalability ensure that Kafka remains a leading choice for organizations looking to harness real-time data streams effectively.

The Edge allows you to analyze and take action on your data. Big Data can be made small and relevant. All your assets can be used to collect sensor data. Connect any sensor, PLC or DCS and Historian. Condition monitoring of remote assets. Industry 4.0 data collection and integration Data flows can combine streaming and enterprise data. You can use your favorite Cloud Provider, or your own data centre for data storage. Crosser Edge MLOps functionality allows you to create, manage, and deploy your own ML models. Crosser Edge Node can run any ML framework. Crosser cloud central resource library for your trained model. Drag-and-drop is used for all other steps of the data pipeline. One operation is all it takes to deploy ML models on any number of Edge Nodes. Crosser Flow Studio enables self-service innovation. A rich library of pre-built modules is available. Facilitates collaboration between teams and sites. No more dependence on a single member of a team.

The Flowcore platform combines event streaming and event sourcing into a single service that is easy to use. Data flow and replayable data storage designed for developers in data-driven startups or enterprises that want to remain at the forefront of growth and innovation. All data operations are efficiently preserved, ensuring that no valuable data will ever be lost. Immediate transformations, reclassifications and loading of your data to any destination. Break free from rigid data structure. Flowcore's scalable architectural design adapts to your business growth and handles increasing volumes of data without difficulty. By streamlining and simplifying backend data processes, you can allow your engineering teams to focus on what they are best at, creating innovative products. Integrate AI technologies better, enhancing your products with smart data-driven solutions. Flowcore was designed with developers in mind but its benefits go beyond the dev team.

Cloud Foundry and Kubernetes support microservice-based streaming and batch processing. Spring Cloud Data Flow allows you to create complex topologies that can be used for streaming and batch data pipelines. The data pipelines are made up of Spring Boot apps that were built using the Spring Cloud Stream and Spring Cloud Task microservice frameworks. Spring Cloud Data Flow supports a variety of data processing use cases including ETL, import/export, event streaming and predictive analytics. Spring Cloud Data Flow server uses Spring Cloud Deployer to deploy data pipelines made from Spring Cloud Stream and Spring Cloud Task applications onto modern platforms like Cloud Foundry or Kubernetes. Pre-built stream and task/batch starter applications for different data integration and processing scenarios allow for experimentation and learning. You can create custom stream and task apps that target different middleware or services using the Spring Boot programming model.

Spark Streaming uses Apache Spark's language-integrated API for stream processing. It allows you to write streaming jobs in the same way as you write batch jobs. It supports Java, Scala, and Python. Spark Streaming recovers lost work as well as operator state (e.g. Without any additional code, Spark Streaming recovers both lost work and operator state (e.g. sliding windows) right out of the box. Spark Streaming allows you to reuse the same code for batch processing and join streams against historical data. You can also run ad-hoc queries about stream state by running on Spark. Spark Streaming allows you to create interactive applications that go beyond analytics. Apache Spark includes Spark Streaming. It is updated with every Spark release. Spark Streaming can be run on Spark's standalone mode or other supported cluster resource mangers. It also has a local run mode that can be used for development. Spark Streaming uses ZooKeeper for high availability in production.

Cloudera DataFlow for the Public Cloud (CDF-PC) is a versatile, cloud-based data distribution solution that utilizes Apache NiFi, enabling developers to seamlessly connect to diverse data sources with varying structures, process that data, and deliver it to a wide array of destinations. This platform features a flow-oriented low-code development approach that closely matches the preferences of developers when creating, developing, and testing their data distribution pipelines. CDF-PC boasts an extensive library of over 400 connectors and processors that cater to a broad spectrum of hybrid cloud services, including data lakes, lakehouses, cloud warehouses, and on-premises sources, ensuring efficient and flexible data distribution. Furthermore, the data flows created can be version-controlled within a catalog, allowing operators to easily manage deployments across different runtimes, thereby enhancing operational efficiency and simplifying the deployment process. Ultimately, CDF-PC empowers organizations to harness their data effectively, promoting innovation and agility in data management.

We know how simple Apache Kafka®, can be when you have the right tools. kPow was created to simplify the Kafka development experience and save businesses time and money. kPow makes it easy to find the root cause of production problems in a matter of clicks and not hours. With kPow's Data Inspect and kREPL functions, you can search tens of thousands messages per second. Are you new to Kafka kPow's Kafka UI is unique and allows developers to quickly understand the core Kafka concepts. You can upskill new members of your team and increase your Kafka knowledge. kPow offers a range of Kafka management features and monitoring capabilities in a single Docker Container. You can manage multiple clusters and schema registries. Connect installs with one instance.

It is difficult, costly, and risky to connect systems to scale AI projects. Pandio's cloud native managed solution simplifies data pipelines to harness AI's power. You can access your data from any location at any time to query, analyze, or drive to insight. Big data analytics without the high cost Enable data movement seamlessly. Streaming, queuing, and pub-sub with unparalleled throughput, latency and durability. In less than 30 minutes, you can design, train, deploy, and test machine learning models locally. Accelerate your journey to ML and democratize it across your organization. It doesn't take months or years of disappointment. Pandio's AI driven architecture automatically orchestrates all your models, data and ML tools. Pandio can be integrated with your existing stack to help you accelerate your ML efforts. Orchestrate your messages and models across your organization.

Akka serves as a comprehensive toolkit designed for creating highly concurrent, distributed, and resilient applications driven by messages, catering to both Java and Scala developers. Complementing this is Akka Insights, a specialized monitoring and observability tool crafted specifically for Akka environments. By utilizing Actors and Streams, developers can construct systems that not only optimize server resource usage but also expand seamlessly across multiple servers. Rooted in the foundational concepts of The Reactive Manifesto, Akka empowers the development of self-healing systems that maintain responsiveness even amid failures, thereby eliminating single points of failure in distributed architectures. It features capabilities for load balancing and adaptive routing among nodes, as well as integrates Event Sourcing and CQRS with Cluster Sharding techniques. Furthermore, it supports Distributed Data for achieving eventual consistency through Conflict-free Replicated Data Types (CRDTs). Akka also facilitates asynchronous, non-blocking stream processing with built-in backpressure management. The fully asynchronous and streaming HTTP server and client capabilities provide an excellent foundation for building microservices, while integrations with Alpakka enhance the streaming capabilities further, allowing for more efficient data handling in complex applications. This makes Akka a versatile choice for modern application development.

IBM Cloud Pak For Integration®, a hybrid integration platform, is an automated, closed-loop system that supports multiple styles and types of integration in a single, unified experience. Connect cloud and on-premise apps to unlock business data and assets, securely move data with enterprise messaging, deliver event interactions, transfer data across all clouds, and deploy and scale with shared foundational services and cloud-native architecture. All this is done with enterprise-grade encryption and security. Automated, closed-loop, and multi-style integrations deliver the best results. Targeted innovations can be used to automate integrations. These include natural language-powered flows, AI-assisted maps and RPA. You can also use company-specific operational information to continuously improve integrations and API test generation. Workload balancing can also be achieved.

The industry's most comprehensive, API-driven, microservices-based, AI-powered enterprise iPaaS is here to help you go beyond the table. IICS is powered by the CLAIRE engine and supports any cloud-native patterns, including data, applications, API integration, MDM, and API integration. Our multi-cloud support and global distribution covers Microsoft Azure, AWS and Google Cloud Platform. Snowflake is also included. IICS has the industry's highest trust and enterprise scale, as well as the industry's highest security certifications. Our enterprise iPaaS offers multiple cloud data management products that can be used to increase productivity, speed up scaling, and increase efficiency. Informatica is a Leader in the Gartner 2020 Magic Quadrant Enterprise iPaaS. Informatica Intelligent Cloud Services reviews and real-world insights are available. Get our cloud services for free. Customers are our number one priority, across products, services, support, and everything in between. We have been able to earn top marks in customer loyalty 12 years running.

Achieve seamless Continuous Intelligence solutions with greater speed, efficiency, and cost-effectiveness, all while minimizing engineering effort. The Cogility Cogynt platform offers a cloud-scalable event stream processing solution that is enriched by sophisticated, AI-driven analytics. With a comprehensive and unified toolset, organizations can efficiently and rapidly implement continuous intelligence solutions that meet their needs. This all-encompassing platform simplifies the deployment process by facilitating the construction of model logic, tailoring the intake of data sources, processing data streams, analyzing, visualizing, and disseminating intelligence insights, as well as auditing and enhancing outcomes while ensuring integration with other applications. Additionally, Cogynt’s Authoring Tool provides an intuitive, no-code design environment that allows users to create, modify, and deploy data models effortlessly. Moreover, the Data Management Tool from Cogynt simplifies the publishing of your model, enabling immediate application to stream data processing and effectively abstracting the complexities of Flink job coding for users. By leveraging these tools, organizations can transform their data into actionable insights with remarkable agility.

We provide a geo-distributed, real-time database, stream processing, and compute runtime for event driven applications across up to 175 global edge data centers. Our platform is loved by API and app developers because it solves the most difficult problems of sharing mutable states across hundreds of locations around the world. We also have high consistency and low latency. Macrometa allows you to surgically expand your existing infrastructure to bring your application closer to your users. This allows you to improve performance and user experience, as well as comply with global data governance laws. Macrometa is a streaming, serverless NoSQL database that can be used for stream data processing, pub/sub, and compute engines. You can create stateful data infrastructure, stateful function & containers for long-running workloads, and process data streams real time. We do the ops and orchestration, you write the code.

Aiven takes the reins on your open-source data infrastructure hosted in the cloud, allowing you to focus on what you excel at: developing applications. While you channel your energy into innovation, we expertly handle the complexities of managing cloud data infrastructure. Our solutions are entirely open source, providing the flexibility to transfer data between various clouds or establish multi-cloud setups. You will have complete visibility into your expenses, with a clear understanding of costs as we consolidate networking, storage, and basic support fees. Our dedication to ensuring your Aiven software remains operational is unwavering; should any challenges arise, you can count on us to resolve them promptly. You can launch a service on the Aiven platform in just 10 minutes and sign up without needing to provide credit card information. Simply select your desired open-source service along with the cloud and region for deployment, pick a suitable plan—which includes $300 in free credits—and hit "Create service" to begin configuring your data sources. Enjoy the benefits of maintaining control over your data while leveraging robust open-source services tailored to your needs. With Aiven, you can streamline your cloud operations and focus on driving your projects forward.

InfinyOn has created a programmable continuous Intelligence platform for data in motion. Infinyon Cloud, unlike other event streaming platforms built on Java is built on Rust. It delivers industry-leading scale and security for real time applications. Ready-to-use programmable connectors to shape data events in real time. Intelligent analytics pipelines can be created that automatically refine, protect, and corroborate events. To notify stakeholders and dispatch events, attach programmable connectors. Each connector can be used to either import or export data. Connectors can be deployed in one way: as a Managed Connector in which Fluvio cluster provision and manages the connector, or as a local connector in which you manually launch it as a Docker container wherever you want it. Connectors are conceptually divided into four stages, each with its own responsibilities.

Nussknacker allows domain experts to use a visual tool that is low-code to help them create and execute real-time decisioning algorithm instead of writing code. It is used to perform real-time actions on data: real-time marketing and fraud detection, Internet of Things customer 360, Machine Learning inferring, and Internet of Things customer 360. A visual design tool for decision algorithm is an essential part of Nussknacker. It allows non-technical users, such as analysts or business people, to define decision logic in a clear, concise, and easy-to-follow manner. With a click, scenarios can be deployed for execution once they have been created. They can be modified and redeployed whenever there is a need. Nussknacker supports streaming and request-response processing modes. It uses Kafka as its primary interface in streaming mode. It supports both stateful processing and stateless processing.

Instaclustr, the Open Source-as a Service company, delivers reliability at scale. We provide database, search, messaging, and analytics in an automated, trusted, and proven managed environment. We help companies focus their internal development and operational resources on creating cutting-edge customer-facing applications. Instaclustr is a cloud provider that works with AWS, Heroku Azure, IBM Cloud Platform, Azure, IBM Cloud and Google Cloud Platform. The company is certified by SOC 2 and offers 24/7 customer support.

IBM Storage for Red Hat OpenShift combines traditional and container storage to make it easier to deploy enterprise-class scale out microservices architectures. Valid for Red Hat OpenShift Kubernetes, IBM Cloud Pak and Red Hat OpenShift. For an integrated experience, it simplifies deployment and management. Red Hat OpenShift environments provide enterprise data protection, automated scheduling, data reuse support, and enterprise data protection. You can block, file, and object data resources. You can quickly deploy what you need, when you need it. IBM Storage for Red Hat OpenShift offers the infrastructure foundation and storage orchestration required to build a robust, agile hybrid cloud environment. IBM supports CSI in its block and file storage families to increase container utilization in Kubernetes environments.

OpenShift and watsonx can be deployed in a single step. Fusion comes in two flexible options that can be tailored to your hybrid cloud requirements. Fusion HCI System is a fully integrated and turnkey platform that allows you to run and maintain all your Red Hat OpenShift on-premises applications. Fusion software can be used anywhere Red Hat OpenShift is available, including on public clouds, on-premises and virtual machines. Integrates hardware with Red Hat OpenShift, reducing setup times and eliminating compatibility issues. This allows you to get containerized applications up-and-running in record time, enabling faster innovation. Simplifies infrastructure for OpenShift apps by enabling platform engineers centrally manage OpenShift. This allows them to streamline operations, optimize resource usage and reduce operational complexity and costs.

Streaming data from operations and transactions is valuable when it is well-understood. SAS Event stream processing includes streaming data quality, analytics, and a vast array SAS and open-source machine learning and high frequency analytics for connecting to, deciphering and cleansing streaming data. It doesn't matter how fast your data moves or how many sources you pull from, all of it is under your control through a single, intuitive interface. You can create patterns and address situations from any aspect of your business, giving the ability to be agile and deal with issues as they arise.

IBM® StreamSets allows users to create and maintain smart streaming data pipelines using an intuitive graphical user interface. This facilitates seamless data integration in hybrid and multicloud environments. IBM StreamSets is used by leading global companies to support millions data pipelines, for modern analytics and intelligent applications. Reduce data staleness, and enable real-time information at scale. Handle millions of records across thousands of pipelines in seconds. Drag-and-drop processors that automatically detect and adapt to data drift will protect your data pipelines against unexpected changes and shifts. Create streaming pipelines for ingesting structured, semistructured, or unstructured data to deliver it to multiple destinations.

Radicalbit Natural Analytics is a DataOps platform that enables Streaming Data Integration as well as Real-time Advanced Analytics. The easiest way to get data to the right people at the right time is the best. RNA offers users the latest technologies in self-service mode. It allows for real-time data processing and takes advantage of Artificial Intelligence solutions to extract value from data. It automates data analysis, which can be laborious. It also helps to communicate important insights and findings in easily understandable formats. You can respond quickly and effectively with real-time situational awareness. You can achieve new levels of efficiency, optimization, and ensure collaboration between siloed groups. You can monitor and manage your models from one central view. Then, deploy your evolving models in seconds. No downtime.

Red Hat® OpenShift® Data Foundation--previously Red Hat OpenShift Container Storage--is software-defined storage for containers. Red Hat OpenShift Data Foundation is the data and storage platform for Red Hat OpenShift. It allows teams to quickly and efficiently deploy applications across clouds. Even developers with limited storage knowledge can provision storage directly from Red Hat OpenShift, without having to switch to a separate interface. To support all types of workloads created in enterprise Kubernetes, data can be formatted as files, blocks, and objects. Our technical experts will work with you to determine the best storage solution for your hybrid cloud and multicloud container deployments.

TIBCO offers industrial-strength software solutions that meet performance, throughput and reliability requirements. They also offer a variety of deployment options and technologies to deliver real-time information where it is needed. The TIBCO platform will allow you to manage and monitor your TIBCO applications, no matter where they are located: in the cloud, on premises, or at the edge. TIBCO builds solutions that are critical to the success of some of the largest companies in the world.

The most innovative cloud database service available, with unmatched data mobility across AWS, Azure and Google Cloud, as well as built-in automation for resource optimization and workload optimization. MongoDB Atlas is a global cloud database service that supports modern applications. Fully managed MongoDB can be deployed across AWS, Google Cloud and Azure. This is possible with best-in class automation and proven practices that ensure availability, scalability and compliance with the highest data security and privacy standards. This is the best way to deploy, scale, and run MongoDB in cloud. MongoDB Atlas provides security controls for all data. Allow enterprise-grade features to be integrated with your existing security protocols or compliance standards. MongoDB Atlas protects your data with preconfigured security features that allow for authentication, authorization and encryption.

Tray.ai, an API integration platform, allows users to innovate and automate their organization without the need for developer resources. Tray.io allows users to connect the entire cloud stack themselves. Tray.ai allows users to build and streamline workflows with an intuitive visual editor. Tray.io empowers users' employees with automated processes. The intelligence behind the first iPaaS, which anyone can use to complete their business processes by using natural language instructions. Tray.ai, a low-code platform for automation, is designed to be used by both technical and non-technical users. It allows them to create sophisticated workflows that allow data movement and actions between multiple applications. Our low-code builders and new Merlin AI are transforming the automation process. They bring together the power and flexibility of flexible, scalable automated; support for advanced logic; and native AI capabilities that anyone can utilize.

Red Hat OpenShift is now available on IBM Cloud. This provides OpenShift developers with a fast and secure method to containerize and deploy enterprise workloads within Kubernetes clusters. OpenShift Container Platform (OCP) is managed by IBM so you can focus on your core tasks. Automated provisioning, configuration and installation of infrastructure (compute and network storage), as well as configuration and installation of OpenShift. Automatic scaling, backups, and failure recovery for OpenShift configurations. Automated upgrades of all components (operating systems, OpenShift components and cluster services), as well as performance tuning and security hardening. Security features include image signing, image deployment enforcement and hardware trust. Also, security patch management and compliance (HIPAA PCI, SOC2, ISO).

SiteWhere infrastructure and Microservices can be deployed on Kubernetes on-premises or on almost any cloud provider. Infrastructure is provided by Apache Kafka, Zookeeper and Hashicorp Consul configured in highly-available configurations. Each microservice scales independently, and integrates itself automatically. Complete multitenant IoT eco-system including device management, big data event storing, REST APIs and data integration. Distributed architecture with Java microservices on Docker infrastructure and Apache Kafka processing pipeline. SiteWhere CE is open source and will always be free for both private and commercial use. The SiteWhere team provides free basic support as well as a constant stream of new features.

Azure Red Hat OpenShift offers fully managed, highly available OpenShift clusters that are provisioned on demand, with joint monitoring and management by Microsoft and Red Hat. At the heart of Red Hat OpenShift lies Kubernetes, which is enhanced by additional features that elevate its functionality, transforming it into a comprehensive container platform as a service (PaaS) that significantly enhances both developer and operator experiences. Users benefit from public and private clusters that are not only highly available but also fully managed, with automated operations and seamless over-the-air platform upgrades. Additionally, the improved user interface within the web console allows for easier application topology and build management, enabling users to efficiently build, deploy, configure, and visualize their containerized applications alongside the associated cluster resources. This integration fosters a more streamlined workflow and accelerates the development lifecycle for teams using container technologies.

Superstream: An AI Solution That Lowers Expenses and Boosts Kafka Performance by 75%, With Zero Modifications to Your Current Infrastructure.