Best Event Stream Processing Software of 2024

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.

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.

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.

High-performing applications need real-time information exchange. This is exactly what TIBCO Cloud™, Messaging software offers. We offer multiple options including Apache Kafka and Apache Pulsar, TIBCO Enterprise Message Services™, TIBCO FLL® or TIBCO eFTL™ software. Whether you need event-driven application integration, high-performance, low latency messaging, connections for web apps and backend systems, or IoT integration, the simple yet robust TIBCO cloud messaging client API and cloud distribution network are the best options. TIBCO Cloud Messaging software offers fault tolerance, multi-zone reliability, and scalable performances. It allows you to concentrate on your application logic and not have to worry about infrastructure or containers being deployed for your event streams. Connect your apps to the API to immediately publish and subscribe to event messages.

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.

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.

The digital age will see billions of people, devices, and systems interact in real time, creating new and disruptive competitive advantages. How can you play there? You can experiment, learn, and rapidly evolve by building distributed, stateful, rule based event-processing platforms. Data is constantly arriving from hundreds of sources, both internal and external. It has a shelf-life and its value decreases over time. TIBCO allows you to jump-start big data processing projects that allow you to sense, reason and respond. This is a different approach than the traditional store analysis, report, act approach. Multiple rule authoring environments allow for collaboration between IT professionals and business professionals.

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.

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

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

In-Memory Computing Platform. Digital world is different. Microseconds are important. The world's most important organizations rely on us for powering their most sensitive applications at scale. If they meet the current requirement for immediate access, new data-enabled apps can transform your business. Hazelcast solutions can be used to complement any database and deliver results that are much faster than traditional systems of record. Hazelcast's distributed architecture ensures redundancy and continuous cluster up-time, as well as always available data to support the most demanding applications. The capacity grows with demand without compromising performance and availability. The cloud delivers the fastest in-memory data grid and third-generation high speed event processing.

TIBCO ComputeDB™ is a memory optimized, Apache Spark-based database. It is able to deliver high throughput, low latency and high concurrency for unified analytics workloads that combine streaming, interactive analysis and artificial intelligence in one, easy-to-manage distributed cluste.

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 analyze, query, and then act at lightning speed on IoT data and other streaming data. Intelligent applications allow you to take real-time operations and analytics up a notch with fast deployments that can be used to quickly take action based on new models and decisions. TIBCO®, Streaming software provides enterprise-grade streaming analytics that can be used in the cloud to quickly build real-time applications. It is much less expensive than other options and has a lower risk.

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

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.

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.

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.

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.

Heron's architecture is rich in architectural improvements that help to increase efficiency. Heron is compatible with Apache Storm API, so no code changes are required to migrate. You can quickly identify and debug topologies issues, which allows for faster development. Heron UI provides a visual overview of each topology, allowing you to see hot spots and detailed counters to track progress and troubleshooting. Heron is highly adaptable in that it can execute large numbers of components for each topology as well as the ability launch and track large amounts of topologies.

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.

Conduktor is the all-in one interface that allows you to interact with the Apache Kafka ecosystem. You can confidently develop and manage Apache Kafka. Conduktor DevTools is the all-in one Apache Kafka desktop client. You can manage Apache Kafka confidently and save time for your whole team. Apache Kafka can be difficult to learn and use. Conduktor is loved by developers for its best-in-class user interface. Conduktor is more than an interface for Apache Kafka. Conduktor gives you and your team control over your entire data pipeline thanks to its integration with many technologies around Apache Kafka. It gives you and your team the most comprehensive tool for Apache Kafka.

Akka is a toolkit that allows you to build highly concurrent, distributed and resilient message-driven Java and Scala applications. Akka Insights, an intelligent monitoring and observability tool, is specifically designed for Akka. Actors and streams allow you to build systems that scale up by using more server resources and out by using multiple servers. You can build systems that self-heal and remain responsive to failures by using the principles of The Reactive Manifesto Akka. Distributed systems that are resilient to failure. Load balancing across nodes and adaptive routing. Cluster Sharding is used for event sourcing and CQRS. Distributed Data to ensure eventual consistency with CRDTs Backpressure and asynchronous stream processing. A great platform for microservice development is the fully async streaming HTTP server and client. Alpakka streams integrations.

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.