Alternatives to Apache Kafka
Compare Apache Kafka alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Apache Kafka in 2024. Compare features, ratings, user reviews, pricing, and more from Apache Kafka competitors and alternatives in order to make an informed decision for your business.
-
1
StarTree
StarTree
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. • Gain critical real-time insights to run your business • Seamlessly integrate data streaming and batch data • High performance in throughput and low-latency at petabyte scale • Fully-managed cloud service • Tiered storage to optimize cloud performance & spend • Fully-secure & enterprise-ready -
2
EMQX
EMQ Technologies
EMQX is the world's most scalable and reliable MQTT messaging platform designed by EMQ. It supports 100M concurrent IoT device connections per cluster while maintaining extremely high throughput and sub-millisecond latency. EMQX boasts more than 20,000 global users from over 50 countries, connecting more than 100M IoT devices worldwide, and is trusted by over 300 customers in mission-critical IoT scenarios, including well-known brands like HPE, VMware, Verifone, SAIC Volkswagen, and Ericsson. Our edge-to-cloud IoT connectivity solutions are flexible to meet the demands of various industries towards digital transformation, including connected vehicles, Industrial IoT, oil & gas, carrier, finance, smart energy, and smart cities.Starting Price: $0.18 per hour -
3
Striim
Striim
Data integration for your hybrid cloud. Modern, reliable data integration across your private and public cloud. All in real-time with change data capture and data streams. Built by the executive & technical team from GoldenGate Software, Striim brings decades of experience in mission-critical enterprise workloads. Striim scales out as a distributed platform in your environment or in the cloud. Scalability is fully configurable by your team. Striim is fully secure with HIPAA and GDPR compliance. Built ground up for modern enterprise workloads in the cloud or on-premise. Drag and drop to create data flows between your sources and targets. Process, enrich, and analyze your streaming data with real-time SQL queries. -
4
Open Automation Software
Open Automation Software
Liberate your Industry 4.0 data with Open Automation Software IIoT platform for Windows and Linux. OAS is truly an unlimited IoT Gateway for Windows, Linux, Raspberry Pi 4, Windows IoT Core, and Docker deployments. Create HMI visualization for web, WPF, and WinForm C# and VB .NET applications. Log data and alarms to SQL Server, Oracle, MS Access, MySQL, Azure SQL, PostgreSQL, Cassandra, MongoDB, MariaDB, SQLite, InfluxDB, and CSV files. MQTT Broker and Client interface along with cloud connectivity to Azure IoT and AWS IoT Gateway. Read and write data from remote Excel Workbooks. Alarm notification to email, SMS text, and voice messaging. .NET and REST API programmatic access. Allen Bradley ControlLogix, CompactLogix, GuardLogix, Micro800, MicroLogix, SLC 500, and PLC-5. Siemens S7-200, S7-300, S7-400, S7-1200, and S7-1500. Modbus TCP, Modbus RTU, and Modbus ASCII for Master and Slave communications. OPTO-22, MTConnect, and OPC UA, OPC DA.Starting Price: $495 one-time payment -
5
Kubernetes
Kubernetes
Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes builds upon 15 years of experience of running production workloads at Google, combined with best-of-breed ideas and practices from the community. Designed on the same principles that allows Google to run billions of containers a week, Kubernetes can scale without increasing your ops team. Whether testing locally or running a global enterprise, Kubernetes flexibility grows with you to deliver your applications consistently and easily no matter how complex your need is. Kubernetes is open source giving you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you effortlessly move workloads to where it matters to you.Starting Price: Free -
6
Apache Flink
Apache Software Foundation
Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale. Any kind of data is produced as a stream of events. Credit card transactions, sensor measurements, machine logs, or user interactions on a website or mobile application, all of these data are generated as a stream. Apache Flink excels at processing unbounded and bounded data sets. Precise control of time and state enable Flink’s runtime to run any kind of application on unbounded streams. Bounded streams are internally processed by algorithms and data structures that are specifically designed for fixed sized data sets, yielding excellent performance. Flink is designed to work well each of the previously listed resource managers. -
7
Cribl AppScope
Cribl
AppScope is a new approach to black-box instrumentation delivering ubiquitous, unified telemetry from any Linux executable by simply prepending scope to the command. Talk to any customer using Application Performance Management, and they’ll tell you how much they love their solution, but they wish they could extend it to more of their applications. Most have 10% or fewer of their apps instrumented for APM, and are supplementing what they can with basic metrics. Where does this leave the other 80%? Enter AppScope. No language-specific instrumentation. No application developers required. AppScope is language agnostic and completely userland; works with any application; scales from the CLI to production. Send AppScope data to any existing monitoring tool, time series database, or log tool. AppScope allows SREs and Ops teams to interrogate running applications to discover how they work and their behavior in any deployment context, from on-prem to cloud to containers. -
8
Google Cloud Dataflow
Google
Unified stream and batch data processing that's serverless, fast, and cost-effective. Fully managed data processing service. Automated provisioning and management of processing resources. Horizontal autoscaling of worker resources to maximize resource utilization. OSS community-driven innovation with Apache Beam SDK. Reliable and consistent exactly-once processing. Streaming data analytics with speed. Dataflow enables fast, simplified streaming data pipeline development with lower data latency. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Allow teams to focus on programming instead of managing server clusters as Dataflow’s serverless approach removes operational overhead from data engineering workloads. Dataflow automates provisioning and management of processing resources to minimize latency and maximize utilization. -
9
Azure Event Grid
Microsoft
Simplify your event-based apps with Event Grid, a single service for managing routing of all events from any source to any destination. Designed for high availability, consistent performance, and dynamic scale, Event Grid lets you focus on your app logic rather than infrastructure. Eliminate polling—and the associated cost and latency. With Event Grid, event publishers are decoupled from event subscribers using a pub/sub model and simple HTTP-based event delivery, allowing you to build scalable serverless applications, microservices, and distributed systems. Gain massive scale, dynamically, while getting near-real-time notifications for changes you’re interested in. Build better, more reliable applications through reactive programming, capitalizing on guaranteed event delivery and the high availability of the cloud. Develop richer application scenarios by connecting multiple possible sources and destinations of events. -
10
Azure Event Hubs
Microsoft
Event Hubs is a fully managed, real-time data ingestion service that’s simple, trusted, and scalable. Stream millions of events per second from any source to build dynamic data pipelines and immediately respond to business challenges. Keep processing data during emergencies using the geo-disaster recovery and geo-replication features. Integrate seamlessly with other Azure services to unlock valuable insights. Allow existing Apache Kafka clients and applications to talk to Event Hubs without any code changes—you get a managed Kafka experience without having to manage your own clusters. Experience real-time data ingestion and microbatching on the same stream. Focus on drawing insights from your data instead of managing infrastructure. Build real-time big data pipelines and respond to business challenges right away.Starting Price: $0.03 per hour -
11
Azure IoT Hub
Microsoft
Managed service for bidirectional communication between IoT devices and Azure. Enable highly secure and reliable communication between your Internet of Things (IoT) application and the devices it manages. Azure IoT Hub provides a cloud-hosted solution back end to connect virtually any device. Extend your solution from the cloud to the edge with per-device authentication, built-in device management, and scaled provisioning. Use device-to-cloud telemetry data to understand the state of your devices and define message routes to other Azure services—without writing any code. In cloud-to-device messages, reliably send commands and notifications to your connected devices and track message delivery with acknowledgement receipts. Automatically resend device messages as needed to accommodate intermittent connectivity. Azure IoT Central: Proof of concept isn’t your endgame. We’ll help you build industry-leading solutions with a hosted IoT application platform.Starting Price: $10 per IoT unit per month -
12
Alooma
Google
Alooma enables data teams to have visibility and control. It brings data from your various data silos together into BigQuery, all in real time. Set up and flow data in minutes or customize, enrich, and transform data on the stream before it even hits the data warehouse. Never lose an event. Alooma's built in safety nets ensure easy error handling without pausing your pipeline. Any number of data sources, from low to high volume, Alooma’s infrastructure scales to your needs. -
13
Amazon EventBridge
Amazon
Amazon EventBridge is a serverless event bus that makes it easy to connect applications together using data from your own applications, integrated Software-as-a-Service (SaaS) applications, and AWS services. EventBridge delivers a stream of real-time data from event sources, such as Zendesk, Datadog, or Pagerduty, and routes that data to targets like AWS Lambda. You can set up routing rules to determine where to send your data to build application architectures that react in real time to all of your data sources. EventBridge makes it easy to build event-driven applications because it takes care of event ingestion and delivery, security, authorization, and error handling for you. As your applications become more interconnected through events, you need to spend more effort to find events and understand their structure in order to write code to react to those events. -
14
Amazon Kinesis
Amazon
Easily collect, process, and analyze video and data streams in real time. Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin. Amazon Kinesis enables you to ingest, buffer, and process streaming data in real-time, so you can derive insights in seconds or minutes instead of hours or days. -
15
Amazon MQ
Amazon
Amazon MQ is a managed message broker service for Apache ActiveMQ that makes it easy to set up and operate message brokers in the cloud. Message brokers allow different software systems–often using different programming languages, and on different platforms–to communicate and exchange information. Amazon MQ reduces your operational load by managing the provisioning, setup, and maintenance of ActiveMQ, a popular open-source message broker. Connecting your current applications to Amazon MQ is easy because it uses industry-standard APIs and protocols for messaging, including JMS, NMS, AMQP, STOMP, MQTT, and WebSocket. Using standards means that in most cases, there’s no need to rewrite any messaging code when you migrate to AWS. With a few clicks in the Amazon MQ Console, Amazon MQ provisions your broker with support for version upgrades, so you can always use the latest version that Amazon MQ supports. Once you configure your broker, your applications can produce and consume messages. -
16
Amazon MSK
Amazon
Amazon MSK is a fully managed service that makes it easy for you to build and run applications that use Apache Kafka to process streaming data. Apache Kafka is an open-source platform for building real-time streaming data pipelines and applications. With Amazon MSK, you can use native Apache Kafka APIs to populate data lakes, stream changes to and from databases, and power machine learning and analytics applications. Apache Kafka clusters are challenging to setup, scale, and manage in production. When you run Apache Kafka on your own, you need to provision servers, configure Apache Kafka manually, replace servers when they fail, orchestrate server patches and upgrades, architect the cluster for high availability, ensure data is durably stored and secured, setup monitoring and alarms, and carefully plan scaling events to support load changes.Starting Price: $0.0543 per hour -
17
Amazon Simple Notification Service (SNS) is a fully managed messaging service for both system-to-system and app-to-person (A2P) communication. It enables you to communicate between systems through publish/subscribe (pub/sub) patterns that enable messaging between decoupled microservice applications or to communicate directly to users via SMS, mobile push and email. The system-to-system pub/sub functionality provides topics for high-throughput, push-based, many-to-many messaging. Using Amazon SNS topics, your publisher systems can fanout messages to a large number of subscriber systems or customer endpoints including Amazon SQS queues, AWS Lambda functions and HTTP/S, for parallel processing. The A2P messaging functionality enables you to send messages to users at scale using either a pub/sub pattern or direct-publish messages using a single API.
-
18
Airbyte
Airbyte
Get all your ELT data pipelines running in minutes, even your custom ones. Let your team focus on insights and innovation. Unify your data integration pipelines in one open-source ELT platform. Airbyte addresses all your data team's connector needs, however custom they are and whatever your scale. The data integration platform that can scale with your custom or high-volume needs. From high-volume databases to the long tail of API sources. Leverage Airbyte’s long tail of high-quality connectors that adapt to schema and API changes. Extensible to unify all native & custom ELT. Edit pre-built open-source connectors, or build new ones with our connector development kit in a few hours. Transparent and scalable pricing. Finally, a transparent and predictable cost-based pricing that scales with your data needs. You don’t need to worry about volume anymore. No more need for custom systems for your in-house scripts or database replication.Starting Price: $2.50 per credit -
19
ActiveMQ
Apache Software Foundation
Apache ActiveMQ® is the most popular open source, multi-protocol, Java-based message broker. It supports industry standard protocols so users get the benefits of client choices across a broad range of languages and platforms. Connect from clients written in JavaScript, C, C++, Python, .Net, and more. Integrate your multi-platform applications using the ubiquitous AMQP protocol. Exchange messages between your web applications using STOMP over websockets. Manage your IoT devices using MQTT. Support your existing JMS infrastructure and beyond. ActiveMQ offers the power and flexibility to support any messaging use-case. There are currently two "flavors" of ActiveMQ available - the well-known "classic" broker and the "next generation" broker code-named Artemis. Once Artemis reaches a sufficient level of feature parity with the "Classic" code-base it will become the next major version of ActiveMQ. Initial migration documentation is available as well as a development roadmap for Artemis. -
20
Anypoint MQ
MuleSoft
With Anypoint MQ, perform advanced asynchronous messaging — such as queueing and pub/sub — with fully hosted and managed cloud message queues and exchanges. As a service of Anypoint Platform™, Anypoint MQ supports environments, business groups, and role-based access control (RBAC) with enterprise-grade functionality. -
21
Apache Airflow
The Apache Software Foundation
Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine. No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows. -
22
Apache Beam
Apache Software Foundation
The easiest way to do batch and streaming data processing. Write once, run anywhere data processing for mission-critical production workloads. Beam reads your data from a diverse set of supported sources, no matter if it’s on-prem or in the cloud. Beam executes your business logic for both batch and streaming use cases. Beam writes the results of your data processing logic to the most popular data sinks in the industry. A simplified, single programming model for both batch and streaming use cases for every member of your data and application teams. Apache Beam is extensible, with projects such as TensorFlow Extended and Apache Hop built on top of Apache Beam. Execute pipelines on multiple execution environments (runners), providing flexibility and avoiding lock-in. Open, community-based development and support to help evolve your application and meet the needs of your specific use cases. -
23
Apache Druid
Druid
Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture. Druid stores and compresses each column individually, and only needs to read the ones needed for a particular query, which supports fast scans, rankings, and groupBys. Druid creates inverted indexes for string values for fast search and filter. Out-of-the-box connectors for Apache Kafka, HDFS, AWS S3, stream processors, and more. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures. -
24
Apache Geode
Apache
Build high-speed, data-intensive applications that elastically meet performance requirements at any scale. Take advantage of Apache Geode's unique technology that blends advanced techniques for data replication, partitioning and distributed processing. Apache Geode provides a database-like consistency model, reliable transaction processing and a shared-nothing architecture to maintain very low latency performance with high concurrency processing. Data can easily be partitioned (sharded) or replicated between nodes allowing performance to scale as needed. Durability is ensured through redundant in-memory copies and disk-based persistence. Super fast write-ahead-logging (WAL) persistence with a shared-nothing architecture that is optimized for fast parallel recovery of nodes or an entire cluster. -
25
Apache Gobblin
Apache Software Foundation
A distributed data integration framework that simplifies common aspects of Big Data integration such as data ingestion, replication, organization, and lifecycle management for both streaming and batch data ecosystems. Runs as a standalone application on a single box. Also supports embedded mode. Runs as an mapreduce application on multiple Hadoop versions. Also supports Azkaban for launching mapreduce jobs. Runs as a standalone cluster with primary and worker nodes. This mode supports high availability and can run on bare metals as well. Runs as an elastic cluster on public cloud. This mode supports high availability. Gobblin as it exists today is a framework that can be used to build different data integration applications like ingest, replication, etc. Each of these applications is typically configured as a separate job and executed through a scheduler like Azkaban. -
26
Apache Heron
Apache Software Foundation
Heron is built with a wide array of architectural improvements that contribute to high-efficiency gains. Heron is API compatible with Apache Storm and hence no code change is required for migration. Easily debug and identify the issues in topologies, allowing faster iteration during development. Heron UI gives a visual overview of each topology to visualize hot spot locations and detailed counters for tracking progress and troubleshooting. Heron is highly scalable both in the ability to execute large number of components for each topology and the ability to launch and track large numbers of topologies. -
27
Apache Ignite
Apache Ignite
Use Ignite as a traditional SQL database by leveraging JDBC drivers, ODBC drivers, or the native SQL APIs that are available for Java, C#, C++, Python, and other programming languages. Seamlessly join, group, aggregate, and order your distributed in-memory and on-disk data. Accelerate your existing applications by 100x using Ignite as an in-memory cache or in-memory data grid that is deployed over one or more external databases. Think of a cache that you can query with SQL, transact, and compute on. Build modern applications that support transactional and analytical workloads by using Ignite as a database that scales beyond the available memory capacity. Ignite allocates memory for your hot data and goes to disk whenever applications query cold records. Execute kilobyte-size custom code over petabytes of data. Turn your Ignite database into a distributed supercomputer for low-latency calculations, complex analytics, and machine learning. -
28
Apache RocketMQ
Apache Software Foundation
Apache RocketMQ™ is a unified messaging engine, lightweight data processing platform. Financial-grade stability, widely used in transaction core links. Seamless connection to surrounding ecosystems such as microservices, real-time computing, and data lakes. Configurable, low-code way to integrate data, can establish connection with any system, can be used to build streaming ETL, data pipeline, data lake, etc. Stream computing engine that provides light weight, high scalability, high performance and rich functions. Rich message type support and message governance methods to meet serverless application scenarios with message granularity load balancing. Apache RocketMQ has been widely adopted by many enterprise developers and cloud vendors due to its simple architecture, rich business functions, and strong scalability. -
29
Apache Spark
Apache Software Foundation
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources. -
30
Apache Storm
Apache Software Foundation
Apache Storm is a free and open source distributed realtime computation system. Apache Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Apache Storm is simple, can be used with any programming language, and is a lot of fun to use! Apache Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Apache Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate. Apache Storm integrates with the queueing and database technologies you already use. An Apache Storm topology consumes streams of data and processes those streams in arbitrarily complex ways, repartitioning the streams between each stage of the computation however needed. Read more in the tutorial. -
31
Fluentd
Fluentd Project
A single, unified logging layer is key to make log data accessible and usable. However, existing tools fall short: legacy tools are not built for new cloud APIs and microservice-oriented architecture in mind and are not innovating quickly enough. Fluentd, created by Treasure Data, solves the challenges of building a unified logging layer with a modular architecture, an extensible plugin model, and a performance optimized engine. In addition to these features, Fluentd Enterprise addresses Enterprise requirements such as Trusted Packaging. Security. Certified Enterprise Connectors, Management / Monitoring, and Enterprise SLA-Based Support, Assurance, and Enterprise Consulting Services -
32
Google Cloud Pub/Sub
Google
Google Cloud Pub/Sub. Scalable, in-order message delivery with pull and push modes. Auto-scaling and auto-provisioning with support from zero to hundreds of GB/second. Independent quota and billing for publishers and subscribers. Global message routing to simplify multi-region systems. High availability made simple. Synchronous, cross-zone message replication and per-message receipt tracking ensure reliable delivery at any scale. No planning, auto-everything. Auto-scaling and auto-provisioning with no partitions eliminate planning and ensures workloads are production-ready from day one. Advanced features, built in. Filtering, dead-letter delivery, and exponential backoff without sacrificing scale help simplify your applications. A fast, reliable way to land small records at any volume, an entry point for real-time and batch pipelines feeding BigQuery, data lakes and operational databases. Use it with ETL/ELT pipelines in Dataflow. -
33
HVR
HVR
A subscription includes everything you need for efficient high-volume data replication and integration. Low-impact data movement even at high volumes with Log-Based Change Data Capture (CDC) and a unique compression algorithm. RESTful APIs enable workflow automation, saving time and streamlining processes. HVR has a variety of security features. Plus it uniquely enables data routing through a firewall proxy in hybrid environments. Supports multi and bi-directional data movement, giving you the freedom to design and optimize your data flows. Everything you need for your data replication project is included under once license. We surround our customers with in-depth training, accessible support, and documentation to foster success. Be confident your data is accurate and in-sync with our Data Validation and Live Compare feature. Everything you need for your data replication project is included under once license. -
34
Hadoop
Apache Software Foundation
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures. A wide variety of companies and organizations use Hadoop for both research and production. Users are encouraged to add themselves to the Hadoop PoweredBy wiki page. Apache Hadoop 3.3.4 incorporates a number of significant enhancements over the previous major release line (hadoop-3.2). -
35
HarperDB
HarperDB
HarperDB is a distributed systems platform that combines database, caching, application, and streaming functions into a single technology. With it, you can start delivering global-scale back-end services with less effort, higher performance, and lower cost than ever before. Deploy user-programmed applications and pre-built add-ons on top of the data they depend on for a high throughput, ultra-low latency back end. Lightning-fast distributed database delivers orders of magnitude more throughput per second than popular NoSQL alternatives while providing limitless horizontal scale. Native real-time pub/sub communication and data processing via MQTT, WebSocket, and HTTP interfaces. HarperDB delivers powerful data-in-motion capabilities without layering in additional services like Kafka. Focus on features that move your business forward, not fighting complex infrastructure. You can't change the speed of light, but you can put less light between your users and their data.Starting Price: Free -
36
Hazelcast
Hazelcast
In-Memory Computing Platform. The digital world is different. Microseconds matter. That's why the world's largest organizations rely on us to power their most time-sensitive applications at scale. New data-enabled applications can deliver transformative business power – if they meet today’s requirement of immediacy. Hazelcast solutions complement virtually any database to deliver results that are significantly faster than a traditional system of record. Hazelcast’s distributed architecture provides redundancy for continuous cluster up-time and always available data to serve the most demanding applications. Capacity grows elastically with demand, without compromising performance or availability. The fastest in-memory data grid, combined with third-generation high-speed event processing, delivered through the cloud. -
37
Oracle Coherence
Oracle
Oracle Coherence is the industry leading in-memory data grid solution that enables organizations to predictably scale mission-critical applications by providing fast access to frequently used data. As data volumes and customer expectations increase, driven by the “internet of things”, social, mobile, cloud and always-connected devices, so does the need to handle more data in real-time, offload over-burdened shared data services and provide availability guarantees. The latest release of Oracle Coherence, 14.1.1, adds a patented scalable messaging implementation, support for polyglot grid-side programming on GraalVM, distributed tracing in the grid, and certification on JDK 11. Coherence stores each piece of data within multiple members (one primary and one or more backup copies), and doesn't consider any mutating operation complete until the backup(s) are successfully created. This ensures that your data grid can tolerate the failure at any level: from single JVM, to whole data center. -
38
Warewolf
Warewolf
Service oriented architecture has finally entered the 21st century. Warewolf allows developers to use a low-code, visual, flow-based, drag and drop environment to design and create microservices, and then call those microservices from directly within their applications. The end result is months of programming accomplished in days and a total revolution in how we think about and use the SOA framework. The beauty of Warewolf is that it doesn't require you to learn anything new. If you've used a drag and drop design tool, then you'll feel right at home with Warewolf. Complex integrations and systems are now as easy to create as a flow chart. Using Warewolf Studio, you'll layout and design your microservices just as you normally would. Then, supply the proper variables and credentials, add any number of connectors where necessary, and call Warewolf from within your application.Starting Price: $50 per month -
39
StreamNative
StreamNative
StreamNative redefines streaming infrastructure by seamlessly integrating Kafka, MQ, and other protocols into a single, unified platform, providing unparalleled flexibility and efficiency for modern data processing needs. StreamNative offers a unified solution that adapts to the diverse requirements of streaming and messaging in a microservices-driven environment. By providing a comprehensive and intelligent approach to messaging and streaming, StreamNative empowers organizations to navigate the complexities and scalability of the modern data ecosystem with efficiency and agility. Apache Pulsar’s unique architecture decouples the message serving layer from the message storage layer to deliver a mature cloud-native data-streaming platform. Scalable and elastic to adapt to rapidly changing event traffic and business needs. Scale-up to millions of topics with architecture that decouples computing and storage.Starting Price: $1,000 per month -
40
StreamSets
StreamSets
StreamSets DataOps Platform. The data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps, and power modern analytics and hybrid integration. Only StreamSets provides a single design experience for all design patterns for 10x greater developer productivity; smart data pipelines that are resilient to change for 80% less breakages; and a single pane of glass for managing and monitoring all pipelines across hybrid and cloud architectures to eliminate blind spots and control gaps. With StreamSets, you can deliver the continuous data that drives the connected enterprise.Starting Price: $1000 per month -
41
KubeMQ
KubeMQ
Innovative and modern message queue and message broker in a lightweight container developed to run in Kubernetes, certified in the CNCF landscape and connect natively to the cloud-native ecosystem. A message broker and message queue ideal for developers. Provides all messaging patterns, scalable, highly available, and secure. Connect microservices instantly using a rich set of connectors without writing any code. Easy-to-use SDKs and elimination of predefined topics, channels, brokers, and routes. Build & Deploy allows configurations of KubeMQ components to be built with a few clicks and deployed with kubectl command line. Innovative and modern message queue and message broker in a lightweight container developed to run in Kubernetes, certified in the CNCF landscape, and connect natively to the cloud-native ecosystem. Simple deployment in Kubernetes in less than 1 minute. Developer friendly by simple to use SDKs and elimination of the many developers and DevOps-centered challenges. -
42
Lightbend
Lightbend
Lightbend provides technology that enables developers to easily build data-centric applications that bring the most demanding, globally distributed applications and streaming data pipelines to life. Companies worldwide turn to Lightbend to solve the challenges of real-time, distributed data in support of their most business-critical initiatives. Akka Platform provides the building blocks that make it easy for businesses to build, deploy, and run large-scale applications that support digitally transformative initiatives. Accelerate time-to-value and reduce infrastructure and cloud costs with reactive microservices that take full advantage of the distributed nature of the cloud and are resilient to failure, highly efficient, and operative at any scale. Native support for encryption, data shredding, TLS enforcement, and continued compliance with GDPR. Framework for quick construction, deployment and management of streaming data pipelines. -
43
NServiceBus
Particular Software
The most developer-friendly service bus for .NET. More than 50,000 developers rely on NServiceBus every day. Backed by a rock-solid distributed development methodology, a worldwide community of experts, consultants and contributors, NServiceBus offers enterprise-grade scalability and reliability for your workflows and integrations without any messy XML configuration - just pure-code bliss. NServiceBus highlights High performance and scalability, Extensively used in many mission-critical systems, business domains and usage scenarios. NServiceBus scalability and performance capabilities are battle-tested and ready for the toughest assignments. Reliable integration with automatic retries. Reliable by default, with built-in configurable mechanisms to retry on failure using messaging best practices and lessons learned from thousands of production usage scenarios. Workflow and background task scheduling. -
44
Logstash
Elasticsearch
Centralize, transform & stash your data. Logstash is a free and open server-side data processing pipeline that ingests data from a multitude of sources, transforms it, and then sends it to your favorite "stash." Logstash dynamically ingests, transforms, and ships your data regardless of format or complexity. Derive structure from unstructured data with grok, decipher geo coordinates from IP addresses, anonymize or exclude sensitive fields, and ease overall processing. Data is often scattered or siloed across many systems in many formats. Logstash supports a variety of inputs that pull in events from a multitude of common sources, all at the same time. Easily ingest from your logs, metrics, web applications, data stores, and various AWS services, all in continuous, streaming fashion. Download: https://sourceforge.net/projects/logstash.mirror/ -
45
Materialize
Materialize
Materialize is a reactive database that delivers incremental view updates. We help developers easily build with streaming data using standard SQL. Materialize can connect to many different external sources of data without pre-processing. Connect directly to streaming sources like Kafka, Postgres databases, CDC, or historical sources of data like 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 maintained and continually updated as new data streams in. With incrementally-updated views, developers can easily build data visualizations or real-time applications. Building with streaming data can be as simple as writing a few lines of SQL.Starting Price: $0.98 per hour -
46
RabbitMQ
RabbitMQ
RabbitMQ is lightweight and easy to deploy on-premises and in the cloud. It supports multiple messaging protocols. RabbitMQ can be deployed in distributed and federated configurations to meet high-scale, high-availability requirements. With tens of thousands of users, RabbitMQ is one of the most popular open-source message brokers. From T-Mobile to Runtastic, RabbitMQ is used worldwide at small startups and large enterprises. RabbitMQ is lightweight and easy to deploy on-premises and in the cloud. It supports multiple messaging protocols. RabbitMQ can be deployed in distributed and federated configurations to meet high-scale, high-availability requirements. RabbitMQ runs on many operating systems and cloud environments and provides a wide range of developer tools for most popular languages. Deploy with Kubernetes, BOSH, Chef, Docker and Puppet. Develop cross-language messaging with favorite programming languages such as Java, .NET, PHP, Python, JavaScript, Ruby, Go, etc.Starting Price: Free -
47
Solace PubSub+
Solace
Solace PubSub+ Platform helps enterprises design, deploy and manage event-driven systems across hybrid and multi-cloud and IoT environments so they can be more event-driven and operate in real-time. The PubSub+ Platform includes the powerful PubSub+ Event Brokers, event management capabilities with PubSub+ Event Portal, as well as monitoring and integration capabilities all available via a single cloud console. PubSub+ allows easy creation of an event mesh, an interconnected network of event brokers, allowing for seamless and dynamic data movement across highly distributed network environments. PubSub+ Event Brokers can be deployed as fully managed cloud services, self-managed software in private cloud or on-premises environments, or as turnkey hardware appliances for unparalleled performance and low TCO. PubSub+ Event Portal is a complimentary toolset for design and governance of event-driven systems including both Solace and Kafka-based event broker environments. -
48
PubNub
PubNub
Innovate with Realtime Features: We take care of realtime communication infrastructure so you can focus on your app. Our Platform for Realtime Communication: A platform to build and operate real-time interactivity for web, mobile, AI/ML, IoT, and Edge computing applications Faster & Easier Deployments: SDK support for 50+ mobile, web, server, and IoT environments (PubNub and community supported) and more than 65 pre-built integrations with external and third-party APIs to give developers the features they need regardless of programming language or tech stack. Scalability: The industry’s most scalable platform capable of supporting millions of concurrent users and allows for rapid growth with low latency, high uptime, and without financial penalties. Security & Compliance: Enterprise-grade security and compliance with the most stringent regulations worldwide, including GDPR, SOC 2, HIPAA, ISO 27001, and CCPA.Starting Price: $0 -
49
Samza
Apache Software Foundation
Samza allows you to build stateful applications that process data in real-time from multiple sources including Apache Kafka. Battle-tested at scale, it supports flexible deployment options to run on YARN or as a standalone library. Samza provides extremely low latencies and high throughput to analyze your data instantly. Scales to several terabytes of state with features like incremental checkpoints and host-affinity. Samza is easy to operate with flexible deployment options - YARN, Kubernetes or standalone. Ability to run the same code to process both batch and streaming data. Integrates with several sources including Kafka, HDFS, AWS Kinesis, Azure Eventhubs, K-V stores and ElasticSearch. -
50
Red Hat AMQ
Red Hat
To respond to business demands quickly and efficiently, you need a way to integrate applications and data spread across your enterprise. Red Hat® AMQ—based on open source communities like Apache ActiveMQ and Apache Kafka—is a flexible messaging platform that delivers information reliably, enabling real-time integration and connecting the Internet of Things (IoT).
