Alternatives to SAS Event Stream Processing

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

Azure Stream Analytics is an easy-to-use, real time analytics service that's designed for mission-critical workloads. In just a few steps, you can create an end-to-end streaming pipeline that is serverless in just a few clicks. SQL--easily extensible and customizable with custom code, built-in machine learning capabilities and more advanced scenarios. You can run the most complex workloads with confidence knowing that your SLA is financially backed.

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.

Event Hubs is a fully managed, real time data ingestion service that is simple, reliable, and scalable. Stream millions of events per minute from any source to create dynamic data pipelines that can be used to respond to business problems. Use the geo-disaster recovery or geo-replication features to continue processing data in emergencies. Integrate seamlessly with Azure services to unlock valuable insights. You can allow existing Apache Kafka clients to talk to Event Hubs with no code changes. This allows you to have a managed Kafka experience, without the need to manage your own clusters. You can experience real-time data input and microbatching in the same stream. Instead of worrying about infrastructure management, focus on gaining insights from your data. Real-time big data pipelines are built to address business challenges immediately.

Amazon MSK is a fully managed service that makes coding and running applications that use Apache Kafka for streaming data processing easy. Apache Kafka is an open source platform that allows you to build real-time streaming data applications and pipelines. Amazon MSK allows you to use native Apache Kafka APIs for populating data lakes, stream changes between databases, and to power machine learning or analytics applications. It is difficult to set up, scale, and manage Apache Kafka clusters in production. Apache Kafka clusters can be difficult to set up and scale on your own.

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.

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.

Apache Kafka®, with Confluent, has an infinite retention. Be infrastructure-enabled, not infrastructure-restricted Legacy technologies require you to choose between being real-time or highly-scalable. Event streaming allows you to innovate and win by being both highly-scalable and real-time. Ever wonder how your rideshare app analyses massive amounts of data from multiple sources in order to calculate real-time ETA. Wondering how your credit card company analyzes credit card transactions from all over the world and sends fraud notifications in real time? Event streaming is the answer. Microservices are the future. A persistent bridge to the cloud can enable your hybrid strategy. Break down silos to demonstrate compliance. Gain real-time, persistent event transport. There are many other options.

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.

AI-powered Informatica Data Engineering streaming allows data engineers to ingest and process real-time streaming data in order to gain actionable insights.

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.

Axual provides Kafka-as-a-Service to DevOps teams. Our intuitive Kafka platform will empower your team to unlock insights, drive decisions and improve productivity. Axual is the ideal solution for enterprises that want to seamlessly integrate data streaming with their core IT infrastructure. Our all-in one Kafka platform was designed to eliminate the requirement for extensive technical skills or knowledge, and provide a ready-made product that delivers all of the benefits of event-streaming without the hassle. The Axual Platform, an all-in-one platform, is designed to simplify and enhance the deployment and management of Apache Kafka real-time streaming data. The Axual Platform offers a wide range of features to meet the needs of modern enterprises. This allows organizations to maximize the potential of data streaming, while minimizing complexity.

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.

KX Streaming Analytics allows you to ingest and store historical and time series data. This data can then be processed, stored, processed, and analyzed instantly to provide analytics, insights, or visualizations. The platform offers the complete lifecycle of data services to ensure that your applications and users can be productive quickly. This includes query processing, query processing, tiering and migration, archiving and data protection. Our advanced analytics and visualization tools are widely used in finance and industry. They allow you to create and execute queries, calculations, aggregations and machine learning on any streaming or historical data. Data can be used across multiple hardware environments and can come from high-volume sources such as clickstreams, radio frequency identification, GPS systems and social networking sites.

You can quickly collect, process, analyze, and analyze video and data streams. Amazon Kinesis makes it easy for you to quickly and easily collect, process, analyze, and interpret streaming data. Amazon Kinesis provides key capabilities to process streaming data at any scale cost-effectively, as well as the flexibility to select the tools that best fit your application's requirements. Amazon Kinesis allows you to ingest real-time data, including video, audio, website clickstreams, application logs, and IoT data for machine learning, analytics, or other purposes. Amazon Kinesis allows you to instantly process and analyze data, rather than waiting for all the data to be collected before processing can begin. Amazon Kinesis allows you to ingest buffer and process streaming data instantly, so you can get insights in seconds or minutes, instead of waiting for hours or days.

You can manage your data from the edge to the cloud with a simple, no-code approach to creating sophisticated streaming applications.

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.

Oracle Stream Analytics makes it possible to analyze and process large amounts of real-time data using complex correlation patterns, enrichment and machine learning. It provides real-time, actionable business insight from streaming data and automates actions to drive agile businesses of today.

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

ScaleOut Digital Twin Streaming Service™ Easily create and deploy real-time twins for streaming analytics Connect with many data sources with Azure & AWS IoT Hubs, Kafka, etc. Maximize situational awareness through live, aggregate analytics. A breakthrough cloud service that simultaneously tracks telemetry across millions of data sources, with "real-time digital twins" -- enabling deep, immediate introspection and state-tracking for thousands of devices. The powerful UI makes deployment easy and displays aggregate analytics in real-time to maximize situational awareness. Ideal for a wide variety of applications, including the Internet of Things, real-time intelligent monitoring and logistics, financial services, and financial services. Simple pricing makes it easy to get started. The ScaleOut Digital Twin Builder software and ScaleOut Digital Twin Streaming Service enable the next generation of stream processing.

Embiot®, a compact, high-performance IoT analytics software agent that can be used for smart sensor and IoT gateway applications, is available. This edge computing application can be integrated directly into devices, smart sensor and gateways but is powerful enough to calculate complex analytics using large amounts of raw data at high speeds. Embiot internally uses a stream processing model in order to process sensor data that arrives at different times and in different order. It is easy to use with its intuitive configuration language, rich in math, stats, and AI functions. This makes it quick and easy to solve any analytics problems. Embiot supports many input methods, including MODBUS and MQTT, REST/XML and REST/JSON. Name/Value, CSV, and REST/XML are all supported. Embiot can send output reports to multiple destinations simultaneously in REST, custom text and MQTT formats. Embiot supports TLS on select input streams, HTTP, and MQTT authentication for security.

Apache Kafka®, is an open-source distributed streaming platform.

Azure Data Explorer provides fast, fully managed data analytics services for real-time analysis of large amounts of data streaming from websites, applications, IoT devices, etc. Ask questions and iteratively analyze data on the fly to improve products and customer experiences, monitor devices, boost operations, and increase profits. Identify patterns, anomalies, or trends quickly in your data. Find answers to your questions quickly and easily by exploring new topics. The optimized cost structure allows you to run as many queries as needed. You can explore new possibilities with your data efficiently. With the fully managed, easy-to-use data analytics service, you can focus on insights and not infrastructure. Rapidly respond to rapidly changing and fast-flowing data. Azure Data Explorer simplifies analytics for all types of streaming data.

Apache Spark™, a unified analytics engine that can handle large-scale data processing, is available. Apache Spark delivers high performance for streaming and batch data. It uses a state of the art DAG scheduler, query optimizer, as well as a physical execution engine. Spark has over 80 high-level operators, making it easy to create parallel apps. You can also use it interactively via the Scala, Python and R SQL shells. Spark powers a number of libraries, including SQL and DataFrames and MLlib for machine-learning, GraphX and Spark Streaming. These libraries can be combined seamlessly in one application. Spark can run on Hadoop, Apache Mesos and Kubernetes. It can also be used standalone or in the cloud. It can access a variety of data sources. Spark can be run in standalone cluster mode on EC2, Hadoop YARN and Mesos. Access data in HDFS and Alluxio.

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.

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.

Real-time analytics on raw data. Live ingest from S3, DynamoDB, DynamoDB and more. Raw data can be accessed as SQL tables. In minutes, you can create amazing data-driven apps and live dashboards. Rockset is a serverless analytics and search engine that powers real-time applications and live dashboards. You can directly work with raw data such as JSON, XML and CSV. Rockset can import data from real-time streams and data lakes, data warehouses, and databases. You can import real-time data without the need to build pipelines. Rockset syncs all new data as it arrives in your data sources, without the need to create a fixed schema. You can use familiar SQL, including filters, joins, and aggregations. Rockset automatically indexes every field in your data, making it lightning fast. Fast queries are used to power your apps, microservices and live dashboards. Scale without worrying too much about servers, shards or pagers.

Apama Streaming Analytics enables organizations to analyze and respond to IoT and fast moving data in real time, allowing them to react intelligently to events as they occur. Apama Community Edition by Software AG is a freemium version that allows users to learn about, develop, and implement streaming analytics applications. Software AG Data & Analytics Platform offers an integrated, modular and end-to-end set of world-class capabilities that are optimized for high-speed data management. It also provides connectivity and integration to all major enterprise data sources. You can choose the capabilities that you require: streaming, predictive, and visual analytics. There is also messaging and integration with other enterprise applications. You can integrate historical and other data to create models and enrich customer data.

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.

IBM® Event Streams, an event-streaming platform built on Apache Kafka open-source software, is a smart app that reacts to events as they occur. Event Streams is based upon years of IBM operational experience running Apache Kafka stream events for enterprises. Event Streams is ideal for mission-critical workloads. You can extend the reach and reach of your enterprise assets by connecting to a variety of core systems and using a scalable RESTAPI. Disaster recovery is made easier by geo-replication and rich security. Use the CLI to take advantage of IBM productivity tools. Replicate data between Event Streams deployments during a disaster-recovery scenario.

BlackLynx accelerators provide analytics power where it is needed, without the need for specialized skills. No matter what analytics ecosystem you have, you can power data-driven businesses with powerful, easy to use heterogeneous computing.

Kapacitor, a native data processing engine in InfluxDB 1.x, is an integral component of the InfluxDB 2.0 platform. Kapacitor is able to process both batch and stream data from InfluxDB. It can also act on these data in real time via its programming language TICKscript. Modern applications need more than operator alerts and dashboarding. They also require the ability to trigger actions. Kapacitor's alerting system uses a publish-subscribe design. Alerts are sent to topics, and subscribers subscribe to a topic. Kapacitor is very flexible and can be used to control your environment. It can perform tasks such as stock reordering and auto-scaling. Kapacitor has a simple plugin architecture (or interface) that allows it integrate with any anomaly detector engine.

Esper Enterprise Edition is a distributed platform for horizontal and linear elastic scalability, fault-tolerant event processing, and fault tolerance.

Deliver Continuous Intelligence Solutions easier, faster and more cost-effectively with less engineering effort. The Cogility Cogynt Platform delivers cloud-scalable, Expert AI-based analytics-powered event stream processing software. A complete integrated toolset allows organizations to deliver continuous intelligence solutions quickly, easily and more efficiently. The end-toend platform streamlines deployment by streamlining model logic, customizing the data source intake, processing of data streams, examining and visualizing intelligence findings, sharing them, auditing, and improving results. Cogynt’s Authoring Tool is a convenient design environment that uses zero-code for creating, updating and deploying data model. Cogynt Data Management Tool allows you to quickly publish your model for immediate application to stream data processing, while abstracting Flink Job Coding.

A cloud database that can scale to handle large streaming data sets. Kinetica harnesses modern vectorized processors to perform orders of magnitude faster for real-time spatial or temporal workloads. In real-time, track and gain intelligence from billions upon billions of moving objects. Vectorization unlocks new levels in performance for analytics on spatial or time series data at large scale. You can query and ingest simultaneously to take action on real-time events. Kinetica's lockless architecture allows for distributed ingestion, which means data is always available to be accessed as soon as it arrives. Vectorized processing allows you to do more with fewer resources. More power means simpler data structures which can be stored more efficiently, which in turn allows you to spend less time engineering your data. Vectorized processing allows for incredibly fast analytics and detailed visualizations of moving objects at large scale.

Transform your data into a live stream that is immediately available and ready for use. Leo makes event sourcing simpler by making it easy for you to create, visualize and monitor your data flows. You no longer have to be restricted by legacy systems once you unlock your data. Your developers and stakeholders will be happy with the dramatically reduced development time. Microservice architectures can be used to innovate and increase agility. Microservices are all about data. To make microservices a reality, an organization must have a reliable and repeatable backbone of data. Your custom app should support full-fledged searching. It won't be difficult to add and maintain a search database if you have the data.

Cumulocity IoT, the #1 low-code, self service IoT platform, is pre-integrated and includes all the tools you need to get fast results: device connectivity, management, application enablement, integration, streaming, and predictive analytics. Your business can no longer depend on proprietary technology. You can connect any "thing" to the IoT platform because it is completely open. You can bring your own hardware and tools and choose the components that fit you best. In minutes, you can be up and running with the IoT. Connect a device to view its data. Create a real-time interactive dashboard. You can create rules to monitor and respond to events. All of this can be done without requiring IT or writing code. You can easily integrate new IoT data into the core enterprise systems, apps and processes that have been running your business for years, again without having to code - for a fluid flow data. You will have more context to make smarter decisions.

Apache Kafka is a fully managed service that offers zero vendor lock-in, as well as all the capabilities you need to build your streaming infrastructure. You can easily set up fully managed Kafka within 10 minutes using our web console, or programmatically through our API, CLI or Terraform provider. Connect it to your existing tech stack using over 30 connectors. You can feel confident in your setup thanks to the service integrations that provide logs and metrics. Fully managed distributed data streaming platform that can be deployed in any cloud. Event-driven applications, near real-time data transfer and pipelines and stream analytics are all possible uses for this platform. Aiven's Apache Kafka is hosted and managed for you. You can create clusters, migrate clouds, upgrade versions, and deploy new nodes all with a single click. All this and more through a simple dashboard.

Upsolver makes it easy to create a governed data lake, manage, integrate, and prepare streaming data for analysis. Only use auto-generated schema on-read SQL to create pipelines. A visual IDE that makes it easy to build pipelines. Add Upserts to data lake tables. Mix streaming and large-scale batch data. Automated schema evolution and reprocessing of previous state. Automated orchestration of pipelines (no Dags). Fully-managed execution at scale Strong consistency guarantee over object storage Nearly zero maintenance overhead for analytics-ready information. Integral hygiene for data lake tables, including columnar formats, partitioning and compaction, as well as vacuuming. Low cost, 100,000 events per second (billions every day) Continuous lock-free compaction to eliminate the "small file" problem. Parquet-based tables are ideal for quick queries.

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.

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.

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.

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.

IBM Streams analyzes a wide range of streaming data, including unstructured text, video and audio, and geospatial and sensor data. This helps organizations to spot opportunities and risks, and make decisions in real-time.

Integrate legacy systems seamlessly into the next-gen cloud or data platforms with one solution. Connect allows you to take control of your data, from mainframe to cloud. Integrate data via batch and real-time input for advanced analytics, comprehensive machinelearning and seamless data migration. Connect draws on the decades of experience Precisely has gained as a leader in mainframe sorting and IBM i data availability security. This allows the company to be a leader in the field of complex data access and integration. Access to all enterprise data is possible for critical business projects. Connect supports a wide range targets and sources for all your ELT/CDC needs.

Apache Flink is a distributed processing engine and framework for stateful computations using unbounded and bounded data streams. Flink can be used in all cluster environments and perform computations at any scale and in-memory speed. A stream of events can be used to produce any type of data. All data, including credit card transactions, machine logs, sensor measurements, and user interactions on a website, mobile app, are generated as streams. Apache Flink excels in processing both unbounded and bound data sets. Flink's runtime can run any type of application on unbounded stream streams thanks to its precise control of state and time. Bounded streams are internal processed by algorithms and data structure that are specifically designed to process fixed-sized data sets. This results in excellent performance. Flink can be used with all of the resource managers previously mentioned.

Responsive apps keep developers motivated and users engaged. With the DataStax Astra streaming service platform, you can meet these ever-increasing demands. DataStax Astra Streaming, powered by Apache Pulsar, is a cloud-native messaging platform and event streaming platform. Astra Streaming lets you build streaming applications on top a multi-cloud, elastically scalable and event streaming platform. Apache Pulsar is the next-generation event streaming platform that powers Astra Streaming. It provides a unified solution to streaming, queuing and stream processing. Astra Streaming complements Astra DB. Astra Streaming allows existing Astra DB users to easily create real-time data pipelines from and to their Astra DB instances. Astra Streaming allows you to avoid vendor lock-in by deploying on any major public cloud (AWS, GCP or Azure) compatible with open source Apache Pulsar.

Xeotek is a powerful desktop and web application that helps companies explore and develop data streams and applications faster. Xeotek KaDeck was created for developers, business users, and operations personnel. KaDeck gives business users, developers, operations, and business users insight into data and processes. This benefits the entire team: less misunderstandings, less work, more transparency. Xeotek KaDeck gives you control over your data streams. You can save hours by getting insights at the application and data level in projects or your day-to-day operations. KaDeck makes it easy to export, filter, transform, and manage data streams. You can run JavaScript (NodeV4) code and transform & create test data. You can also view & modify consumer offsets. Manage your streams or topics, Kafka Connect instance, schema registry, ACLs, and Kafka Connect topics from one user interface.

Materialize is a reactive database that provides incremental view updates. Our standard SQL allows developers to easily work with streaming data. Materialize connects to many external data sources without any pre-processing. Connect directly to streaming sources such as Kafka, Postgres databases and CDC or historical data sources such as files or S3. Materialize allows you to query, join, and transform data sources in standard SQL - and presents the results as incrementally-updated Materialized views. Queries are kept current and updated as new data streams are added. With incrementally-updated views, developers can easily build data visualizations or real-time applications. It is as easy as writing a few lines SQL to build with streaming data.

Red Hat®, OpenShift®, Streams for Apache Kafka provides a simplified developer experience for building, scaling, and modernizing cloud-native apps or upgrading existing systems. Red Hat OpenShift streams for Apache Kafka make it easy to create, discover and connect to real-time data stream no matter where they're deployed. Streams are essential for delivering event-driven or data analytics applications. The seamless operation of distributed microservices, large data transfers volumes, and managed operations allow teams to focus on their strengths, speed up value, and lower operating costs. OpenShift streams for Apache Kafka is part of the Red Hat OpenShift product range, which allows you to build a wide variety of data-driven solutions.