Alternatives to Aiven for Apache Kafka

Compare Aiven for Apache Kafka alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Aiven for Apache Kafka in 2026. Compare features, ratings, user reviews, pricing, and more from Aiven for Apache Kafka competitors and alternatives in order to make an informed decision for your business.

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    MongoDB Atlas
    The most innovative cloud database service on the market, with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more. MongoDB Atlas is the global cloud database service for modern applications. Deploy fully managed MongoDB across AWS, Google Cloud, and Azure with best-in-class automation and proven practices that guarantee availability, scalability, and compliance with the most demanding data security and privacy standards. The best way to deploy, run, and scale MongoDB in the cloud. MongoDB Atlas offers built-in security controls for all your data. Enable enterprise-grade features to integrate with your existing security protocols and compliance standards. With MongoDB Atlas, your data is protected with preconfigured security features for authentication, authorization, encryption, and more.
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  • 2
    StarTree

    StarTree

    StarTree

    StarTree, powered by Apache Pinot™, is a fully managed real-time analytics platform built for customer-facing applications that demand instant insights on the freshest data. Unlike traditional data warehouses or OLTP databases—optimized for back-office reporting or transactions—StarTree is engineered for real-time OLAP at true scale, meaning: - Data Volume: query performance sustained at petabyte scale - Ingest Rates: millions of events per second, continuously indexed for freshness - Concurrency: thousands to millions of simultaneous users served with sub-second latency With StarTree, businesses deliver always-fresh insights at interactive speed, enabling applications that personalize, monitor, and act in real time.
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    kPow

    kPow

    Factor House

    We know how easy Apache Kafka® can be with the right tools. We built kPow to make the developer experience with Kafka simple and enjoyable, and to save businesses time and money while growing their Kafka expertise. kPow allows you to get to the heart of production issues in clicks, not hours. Search tens of thousands of messages a second with kPow’s powerful Data Inspect and kREPL functions. New to Kafka? kPow’s unique Kafka UI allows developers to quickly and easily understand core Kafka concepts and gotchas. Upskill new team members, and grow your internal Kafka expertise. kPow provides a suite of Kafka management and monitoring features in a single Docker Container or JAR file. Manage multiple clusters, schema registries, and connect installs with one instance.
    Starting Price: $2,650 per cluster per year
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    Amazon MSK
    Amazon Managed Streaming for Apache Kafka (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
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    Azure Event Hubs
    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
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    IBM Event Streams
    IBM Event Streams is a fully managed event streaming platform built on Apache Kafka, designed to help enterprises process and respond to real-time data streams. With capabilities for machine learning integration, high availability, and secure cloud deployment, it enables organizations to create intelligent applications that react to events as they happen. The platform supports multi-cloud environments, disaster recovery, and geo-replication, making it ideal for mission-critical workloads. IBM Event Streams simplifies building and scaling real-time, event-driven solutions, ensuring data is processed quickly and efficiently.
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    Apache Kafka

    Apache Kafka

    The Apache Software Foundation

    Apache Kafka® is an open-source, distributed streaming platform. Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing. Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages.
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    Axual

    Axual

    Axual

    Axual is Kafka-as-a-Service for DevOps teams. Empower your team to unlock insights and drive decisions with our intuitive Kafka platform. Axual offers the ultimate solution for enterprises looking to seamlessly integrate data streaming into their core IT infrastructure. Our all-in-one Kafka platform is designed to eliminate the need for extensive technical knowledge or skills, and provides a ready-made solution that delivers all the benefits of event streaming without the hassle. The Axual Platform is a all-in-one solution, designed to help you simplify and enhance the deployment, management, and utilization of real-time data streaming with Apache Kafka. By providing an array of features that cater to the diverse needs of modern enterprises, the Axual Platform enables organizations to harness the full potential of data streaming while minimizing complexity and operational overhead.
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    Confluent

    Confluent

    Confluent

    Infinite retention for Apache Kafka® with Confluent. Be infrastructure-enabled, not infrastructure-restricted Legacy technologies require you to choose between being real-time or highly-scalable. Event streaming enables you to innovate and win - by being both real-time and highly-scalable. Ever wonder how your rideshare app analyzes massive amounts of data from multiple sources to calculate real-time ETA? Ever wonder how your credit card company analyzes millions of credit card transactions across the globe and sends fraud notifications in real-time? The answer is event streaming. Move to microservices. Enable your hybrid strategy through a persistent bridge to cloud. Break down silos to demonstrate compliance. Gain real-time, persistent event transport. The list is endless.
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    Red Hat OpenShift Streams
    Red Hat® OpenShift® Streams for Apache Kafka is a managed cloud service that provides a streamlined developer experience for building, deploying, and scaling new cloud-native applications or modernizing existing systems. Red Hat OpenShift Streams for Apache Kafka makes it easy to create, discover, and connect to real-time data streams no matter where they are deployed. Streams are a key component for delivering event-driven and data analytics applications. The combination of seamless operations across distributed microservices, large data transfer volumes, and managed operations allows teams to focus on team strengths, speed up time to value, and lower operational costs. OpenShift Streams for Apache Kafka includes a Kafka ecosystem and is part of a family of cloud services—and the Red Hat OpenShift product family—which helps you build a wide range of data-driven solutions.
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    Conduktor

    Conduktor

    Conduktor

    We created Conduktor, the all-in-one friendly interface to work with the Apache Kafka ecosystem. Develop and manage Apache Kafka with confidence. With Conduktor DevTools, the all-in-one Apache Kafka desktop client. Develop and manage Apache Kafka with confidence, and save time for your entire team. Apache Kafka is hard to learn and to use. Made by Kafka lovers, Conduktor best-in-class user experience is loved by developers. Conduktor offers more than just an interface over Apache Kafka. It provides you and your teams the control of your whole data pipeline, thanks to our integration with most technologies around Apache Kafka. Provide you and your teams the most complete tool on top of Apache Kafka.
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    Google Cloud Managed Service for Kafka
    ​Google Cloud's Managed Service for Apache Kafka is a fully managed and scalable service that simplifies the deployment, management, and maintenance of Apache Kafka clusters. It automates operational tasks such as provisioning, patching, and scaling, allowing users to focus on building applications without the complexities of infrastructure management. It ensures high availability and reliability by replicating data across multiple zones, safeguarding against potential failures. It also offers seamless integration with other Google Cloud services, enabling users to create robust data processing pipelines. Security is a priority, with features like encryption at rest and in transit, identity, and access management, and network isolation to protect data. Google Cloud Managed Service for Kafka supports both public and private networking configurations, providing flexibility in connectivity options.
    Starting Price: $0.09 per hour
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    Astra Streaming
    Responsive applications keep users engaged and developers inspired. Rise to meet these ever-increasing expectations with the DataStax Astra Streaming service platform. DataStax Astra Streaming is a cloud-native messaging and event streaming platform powered by Apache Pulsar. Astra Streaming allows you to build streaming applications on top of an elastically scalable, multi-cloud messaging and event streaming platform. Astra Streaming is powered by Apache Pulsar, the next-generation event streaming platform which provides a unified solution for streaming, queuing, pub/sub, and stream processing. Astra Streaming is a natural complement to Astra DB. Using Astra Streaming, existing Astra DB users can easily build real-time data pipelines into and out of their Astra DB instances. With Astra Streaming, avoid vendor lock-in and deploy on any of the major public clouds (AWS, GCP, Azure) compatible with open-source Apache Pulsar.
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    WarpStream

    WarpStream

    WarpStream

    WarpStream is an Apache Kafka-compatible data streaming platform built directly on top of object storage, with no inter-AZ networking costs, no disks to manage, and infinitely scalable, all within your VPC. WarpStream is deployed as a stateless and auto-scaling agent binary in your VPC with no local disks to manage. Agents stream data directly to and from object storage with no buffering on local disks and no data tiering. Create new “virtual clusters” in our control plane instantly. Support different environments, teams, or projects without managing any dedicated infrastructure. WarpStream is protocol compatible with Apache Kafka, so you can keep using all your favorite tools and software. No need to rewrite your application or use a proprietary SDK. Just change the URL in your favorite Kafka client library and start streaming. Never again have to choose between reliability and your budget.
    Starting Price: $2,987 per month
  • 15
    PubSub+ Platform
    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.
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    Aiven

    Aiven

    Aiven

    Aiven manages your open source data infrastructure in the cloud - so you don't have to. Developers can do what they do best: create applications. We do what we do best: manage cloud data infrastructure. All solutions are open source. You can also freely move data between clouds or create multi-cloud environments. Know exactly how much you’ll be paying and why. We bundle networking, storage and basic support costs together. We are committed to keeping your Aiven software online. If there’s ever an issue, we’ll be there to fix it. Deploy a service on the Aiven platform in 10 minutes. Sign up - no credit card info needed. Select your open source service, and the cloud and region to deploy to. Choose your plan - you have $300 in free credits. Click "Create service" and go on to configure your data sources. Stay in control of your data using powerful open-source services.
    Starting Price: $200.00 per month
  • 17
    DataStax

    DataStax

    DataStax

    The Open, Multi-Cloud Stack for Modern Data Apps. Built on open-source Apache Cassandra™. Global-scale and 100% uptime without vendor lock-in. Deploy on multi-cloud, on-prem, open-source, and Kubernetes. Elastic and pay-as-you-go for improved TCO. Start building faster with Stargate APIs for NoSQL, real-time, reactive, JSON, REST, and GraphQL. Skip the complexity of multiple OSS projects and APIs that don’t scale. Ideal for commerce, mobile, AI/ML, IoT, microservices, social, gaming, and richly interactive applications that must scale-up and scale-down with demand. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Use REST, GraphQL, JSON with your favorite full-stack framework Richly interactive apps that are elastic and viral-ready from Day 1. Pay-as-you-go Apache Cassandra DBaaS that scales effortlessly and affordably.
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    Oracle Cloud Infrastructure Streaming
    Streaming service is a real-time, serverless, Apache Kafka-compatible event streaming platform for developers and data scientists. Streaming is tightly integrated with Oracle Cloud Infrastructure (OCI), Database, GoldenGate, and Integration Cloud. The service also provides out-of-the-box integrations for hundreds of third-party products across categories such as DevOps, databases, big data, and SaaS applications. Data engineers can easily set up and operate big data pipelines. Oracle handles all infrastructure and platform management for event streaming, including provisioning, scaling, and security patching. With the help of consumer groups, Streaming can provide state management for thousands of consumers. This helps developers easily build applications at scale.
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    DeltaStream

    DeltaStream

    DeltaStream

    DeltaStream is a unified serverless stream processing platform that integrates with streaming storage services. Think about it as the compute layer on top of your streaming storage. It provides functionalities of streaming analytics(Stream processing) and streaming databases along with additional features to provide a complete platform to manage, process, secure and share streaming data. DeltaStream provides a SQL based interface where you can easily create stream processing applications such as streaming pipelines, materialized views, microservices and many more. It has a pluggable processing engine and currently uses Apache Flink as its primary stream processing engine. DeltaStream is more than just a query processing layer on top of Kafka or Kinesis. It brings relational database concepts to the data streaming world, including namespacing and role based access control enabling you to securely access, process and share your streaming data regardless of where they are stored.
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    StreamNative

    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
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    IBM Event Automation
    ​IBM Event Automation is a fully composable event-driven solution designed to enable users to detect situations, act in real time, automate decisions, and maximize revenue potential. It allows businesses to respond in real time using Apache Flink, leveraging AI to anticipate critical business patterns. It facilitates the development of scalable applications to meet evolving business needs and handle increasing workloads seamlessly. It enables self-service access with approval controls, field redaction, and schema filtering, enforced by a Kafka-native event gateway via policy administration. IBM Event Automation unifies and accelerates event management by using policy administration for self-service access, enabling control definitions for approval processes, field-level redaction, and schema-based filtering. Use cases include transaction data analysis, inventory optimization, detecting suspicious activity, enhancing customer understanding, predictive maintenance, etc.
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    Superstream

    Superstream

    Superstream

    Superstream Is An AI-based Engine That Reduces Your Kafka Expenses And Boosts Its Performance by 75% Without Changing a Single Component or Your Existing Kafka!
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    SiteWhere

    SiteWhere

    SiteWhere

    SiteWhere infrastructure and microservices are deployed on Kubernetes, allowing for deployment on-premise or almost any cloud provider. Highly-available configurations of Apache Kafka, Zookeeper, and Hashicorp Consul provide infrastructure. Each microservice scales independently and integrates automatically. Complete multitenant IoT ecosystem including device management, event ingestion, big data event storage, REST APIs, data integration, and much more. Distributed architecture built with Java microservices running on Docker infrastructure with Apache Kafka processing pipeline. SiteWhere CE will always be open source and free for private as well as commercial use. The SiteWhere team offers free basic support and a steady stream of new features.
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    DoubleCloud

    DoubleCloud

    DoubleCloud

    Save time & costs by streamlining data pipelines with zero-maintenance open source solutions. From ingestion to visualization, all are integrated, fully managed, and highly reliable, so your engineers will love working with data. You choose whether to use any of DoubleCloud’s managed open source services or leverage the full power of the platform, including data storage, orchestration, ELT, and real-time visualization. We provide leading open source services like ClickHouse, Kafka, and Airflow, with deployment on Amazon Web Services or Google Cloud. Our no-code ELT tool allows real-time data syncing between systems, fast, serverless, and seamlessly integrated with your existing infrastructure. With our managed open-source data visualization you can simply visualize your data in real time by building charts and dashboards. We’ve designed our platform to make the day-to-day life of engineers more convenient.
    Starting Price: $0.024 per 1 GB per month
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    Yandex Managed Service for Apache Kafka
    Focus on developing data stream processing applications and don’t waste time maintaining the infrastructure. Managed Service for Apache Kafka is responsible for managing Zookeeper brokers and clusters, configuring clusters, and updating their versions. Distribute your cluster brokers across different availability zones and set the replication factor to ensure the desired level of fault tolerance. The service analyzes the metrics and status of the cluster and automatically replaces it if one of the nodes fails. For each topic, you can set the replication factor, log cleanup policy, compression type, and maximum number of messages to make better use of computing, network, and disk resources. You can add brokers to your cluster with just a click of a button to improve its performance, or change the class of high-availability hosts without stopping them or losing any data.
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    Lenses

    Lenses

    Lenses.io

    Enable everyone to discover and observe streaming data. Sharing, documenting and cataloging your data can increase productivity by up to 95%. Then from data, build apps for production use cases. Apply a data-centric security model to cover all the gaps of open source technology, and address data privacy. Provide secure and low-code data pipeline capabilities. Eliminate all darkness and offer unparalleled observability in data and apps. Unify your data mesh and data technologies and be confident with open source in production. Lenses is the highest rated product for real-time stream analytics according to independent third party reviews. With feedback from our community and thousands of engineering hours invested, we've built features that ensure you can focus on what drives value from your real time data. Deploy and run SQL-based real time applications over any Kafka Connect or Kubernetes infrastructure including AWS EKS.
    Starting Price: $49 per month
  • 27
    Macrometa

    Macrometa

    Macrometa

    We deliver a geo-distributed real-time database, stream processing and compute runtime for event-driven applications across up to 175 worldwide edge data centers. App & API builders love our platform because we solve the hardest problems of sharing mutable state across 100s of global locations, with strong consistency & low latency. Macrometa enables you to surgically extend your existing infrastructure to bring part of or your entire application closer to your end users. This allows you to improve performance, user experience, and comply with global data governance laws. Macrometa is a serverless, streaming NoSQL database, with integrated pub/sub and stream data processing and compute engine. Create stateful data infrastructure, stateful functions & containers for long running workloads, and process data streams in real time. You do the code, we do all the ops and orchestration.
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    Waterstream

    Waterstream

    SimpleMatter

    Waterstream turns your Kafka-compatible platform into a full-fledged MQTT broker. Connect millions of clients to your data streaming platform with no code, no integration pipelines, and no additional storage. Waterstream implements a bidirectional layer between Kafka and MQTT clients. Forget managing external MQTT clusters, integration pipelines to code, and data duplication. Waterstream scales out linearly. For most operations, its nodes don’t depend on each other. Add more instances to support an increasing number of clients. Waterstream requires only Kafka to operate. The built-in persistence benefits of using Kafka are all included: high availability, high throughput, and low latency.
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    Aiven for PostgreSQL
    Fully managed and hosted PostgreSQL with high performance and all the extensions you want out of the box. Set up fully managed PostgreSQL in less than 10 minutes — directly from our web console or programmatically via our API, CLI, Terraform provider or Kubernetes operator. Our stand-by nodes act automatically as read replicas, and you can also create additional read replicas in different public clouds and regions, even building multi-cloud architectures. Our Point-In-Time-Recovery lets you restore your data to any time within your selected retention period. A fully managed SQL relational database, deployable in the cloud of your choice. Known for reliability, a robust set of features, and exceptionally high performance. Fits well for almost any case, such as creating location-based services, mission critical business applications or simply as a general transactional database.
    Starting Price: $19 per month
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    Google Cloud Dataflow
    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.
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    Samza

    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.
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    Eclipse Streamsheets
    Build professional applications to automate workflows, continuously monitor operations, and control processes in real-time. Your solutions run 24/7 on servers in the cloud and on the edge. Thanks to the spreadsheet user interface, you do not have to be a software developer. Instead of writing program code, you drag-and-drop data, fill cells with formulas, and design charts in a way you already know. Find all necessary protocols on board that you need to connect to sensors, and machines like MQTT, REST, and OPC UA. Streamsheets is native to stream data processing like MQTT and kafka. Pick up a topic stream, transform it and blast it back out into the endless streaming world. REST opens you the world, Streamsheets let you connect to any web service or let them connect to you. Streamsheets run in the cloud, on your servers, but also on edge devices like a Raspberry Pi.
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    Airy Messenger
    From Conversational AI assistants to customer service experiences, own your own conversational platform with open-source Airy. Airy Core is an open source, fully-featured, production-ready conversational platform. With Airy you can process conversational data from a variety of sources. Since Airy's infrastructure is built around Apache Kafka, it can process a large amount of conversations and messages simultaneously and stream the relevant conversational data to wherever you need it. Connect anything from our free open-source live chat plugin to Facebook Messenger & Google's Business Messages to your Airy Core. This is all possible through an ingestion platform that heavily relies on Apache Kafka to process incoming webhook data from different sources. We make sense of the data and reshape it into source-independent contacts, conversations, and messages.
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    Spark Streaming

    Spark Streaming

    Apache Software Foundation

    Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part. By running on Spark, Spark Streaming lets you reuse the same code for batch processing, join streams against historical data, or run ad-hoc queries on stream state. Build powerful interactive applications, not just analytics. Spark Streaming is developed as part of Apache Spark. It thus gets tested and updated with each Spark release. You can run Spark Streaming on Spark's standalone cluster mode or other supported cluster resource managers. It also includes a local run mode for development. In production, Spark Streaming uses ZooKeeper and HDFS for high availability.
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    Instaclustr

    Instaclustr

    Instaclustr

    Instaclustr is the Open Source-as-a-Service company, delivering reliability at scale. We operate an automated, proven, and trusted managed environment, providing database, analytics, search, and messaging. We enable companies to focus internal development and operational resources on building cutting edge customer-facing applications. Instaclustr works with cloud providers including AWS, Heroku, Azure, IBM Cloud, and Google Cloud Platform. The company has SOC 2 certification and provides 24/7 customer support.
    Starting Price: $20 per node per month
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    Baidu Messaging System
    Baidu Messaging System (BMS) is a distributed and scalable hosting message queue service with high throughputs. It collects massive data from websites, devices, or applications for real-time analysis, such as user browsing, clicks, and searches. BMS is a hosted service based on Apache Kafka. Kafka is a distributed, multi-partition, and multi-replica messaging service. The producer asynchronously interacts with the consumer through the message queue without waiting for each other. Compared with the traditional messaging service. BMS encapsulates the Kafka cluster details and provides them in the form of a hosted service. You can directly use BMS to integrate with massively distributed applications without the consideration of cluster operations and pay-per-use only.
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    Nussknacker

    Nussknacker

    Nussknacker

    Nussknacker is a low-code visual tool for domain experts to define and run real-time decisioning algorithms instead of implementing them in the code. It serves where real-time actions on data have to be made: real-time marketing, fraud detection, Internet of Things, Customer 360, and Machine Learning inferring. An essential part of Nussknacker is a visual design tool for decision algorithms. It allows not-so-technical users – analysts or business people – to define decision logic in an imperative, easy-to-follow, and understandable way. Once authored, with a click of a button, scenarios are deployed for execution. And can be changed and redeployed anytime there’s a need. Nussknacker supports two processing modes: streaming and request-response. In streaming mode, it uses Kafka as its primary interface. It supports both stateful and stateless processing.
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    Stackable

    Stackable

    Stackable

    The Stackable data platform was designed with openness and flexibility in mind. It provides you with a curated selection of the best open source data apps like Apache Kafka, Apache Druid, Trino, and Apache Spark. While other current offerings either push their proprietary solutions or deepen vendor lock-in, Stackable takes a different approach. All data apps work together seamlessly and can be added or removed in no time. Based on Kubernetes, it runs everywhere, on-prem or in the cloud. stackablectl and a Kubernetes cluster are all you need to run your first stackable data platform. Within minutes, you will be ready to start working with your data. Configure your one-line startup command right here. Similar to kubectl, stackablectl is designed to easily interface with the Stackable Data Platform. Use the command line utility to deploy and manage stackable data apps on Kubernetes. With stackablectl, you can create, delete, and update components.
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    Altinity

    Altinity

    Altinity

    Altinity's expert engineering team can implement everything from core ClickHouse features to Kubernetes operator behavior to client library improvements. A flexible docker-based GUI manager for ClickHouse that can do the following: Install ClickHouse clusters; Add, delete, and replace nodes; Monitor cluster status; Help with troubleshooting and diagnostics. 3rd party tools and software integrations: Ingest: Kafka, ClickTail; APIs: Python, Golang, ODBC, Java; Kubernetes; UI tools: Grafana, Superset, Tabix, Graphite; Databases: MySQL, PostgreSQL; BI tools: Tableau and many more. Altinity.Cloud incorporates lessons from helping hundreds of customers operate ClickHouse-based analytics. Altinity.Cloud has a Kubernetes-based architecture that delivers portability and user choice of where to operate. Designed from the beginning to run anywhere without lock-in. Cost management is critical for SaaS businesses.
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    E-MapReduce
    EMR is an all-in-one enterprise-ready big data platform that provides cluster, job, and data management services based on open-source ecosystems, such as Hadoop, Spark, Kafka, Flink, and Storm. Alibaba Cloud Elastic MapReduce (EMR) is a big data processing solution that runs on the Alibaba Cloud platform. EMR is built on Alibaba Cloud ECS instances and is based on open-source Apache Hadoop and Apache Spark. EMR allows you to use the Hadoop and Spark ecosystem components, such as Apache Hive, Apache Kafka, Flink, Druid, and TensorFlow, to analyze and process data. You can use EMR to process data stored on different Alibaba Cloud data storage service, such as Object Storage Service (OSS), Log Service (SLS), and Relational Database Service (RDS). You can quickly create clusters without the need to configure hardware and software. All maintenance operations are completed on its Web interface.
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    HStreamDB
    A streaming database is purpose-built to ingest, store, process, and analyze massive data streams. It is a modern data infrastructure that unifies messaging, stream processing, and storage to help get value out of your data in real-time. Ingest massive amounts of data continuously generated from various sources, such as IoT device sensors. Store millions of data streams reliably in a specially designed distributed streaming data storage cluster. Consume data streams in real-time as fast as from Kafka by subscribing to topics in HStreamDB. With the permanent data stream storage, you can playback and consume data streams anytime. Process data streams based on event-time with the same familiar SQL syntax you use to query data in a relational database. You can use SQL to filter, transform, aggregate, and even join multiple data streams.
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    Equalum

    Equalum

    Equalum

    Equalum’s continuous data integration & streaming platform is the only solution that natively supports real-time, batch, and ETL use cases under one, unified platform with zero coding required. Make the move to real-time with a fully orchestrated, drag-and-drop, no-code UI. Experience rapid deployment, powerful transformations, and scalable streaming data pipelines in minutes. Multi-modal, robust, and scalable CDC enabling real-time streaming and data replication. Tuned for best-in-class performance no matter the source. The power of open-source big data frameworks, without the hassle. Equalum harnesses the scalability of open-source data frameworks such as Apache Spark and Kafka in the Platform engine to dramatically improve the performance of streaming and batch data processes. Organizations can increase data volumes while improving performance and minimizing system impact using this best-in-class infrastructure.
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    Spring Cloud Data Flow
    Microservice-based streaming and batch data processing for Cloud Foundry and Kubernetes. Spring Cloud Data Flow provides tools to create complex topologies for streaming and batch data pipelines. The data pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. Spring Cloud Data Flow supports a range of data processing use cases, from ETL to import/export, event streaming, and predictive analytics. The Spring Cloud Data Flow server uses Spring Cloud Deployer, to deploy data pipelines made of Spring Cloud Stream or Spring Cloud Task applications onto modern platforms such as Cloud Foundry and Kubernetes. A selection of pre-built stream and task/batch starter apps for various data integration and processing scenarios facilitate learning and experimentation. Custom stream and task applications, targeting different middleware or data services, can be built using the familiar Spring Boot style programming model.
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    Keen

    Keen

    Keen.io

    Keen is the fully managed event streaming platform. Built upon trusted Apache Kafka, we make it easier than ever for you to collect massive volumes of event data with our real-time data pipeline. Use Keen’s powerful REST API and SDKs to collect event data from anything connected to the internet. Our platform allows you to store your data securely decreasing your operational and delivery risk with Keen. With storage infrastructure powered by Apache Cassandra, data is totally secure through transfer through HTTPS and TLS, then stored with multi-layer AES encryption. Once data is securely stored, utilize our Access Keys to be able to present data in arbitrary ways without having to re-architect your security or data model. Or, take advantage of Role-based Access Control (RBAC), allowing for completely customizable permission tiers, down to specific data points or queries.
    Starting Price: $149 per month
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    Arroyo

    Arroyo

    Arroyo

    Scale from zero to millions of events per second. Arroyo ships as a single, compact binary. Run locally on MacOS or Linux for development, and deploy to production with Docker or Kubernetes. Arroyo is a new kind of stream processing engine, built from the ground up to make real-time easier than batch. Arroyo was designed from the start so that anyone with SQL experience can build reliable, efficient, and correct streaming pipelines. Data scientists and engineers can build end-to-end real-time applications, models, and dashboards, without a separate team of streaming experts. Transform, filter, aggregate, and join data streams by writing SQL, with sub-second results. Your streaming pipelines shouldn't page someone just because Kubernetes decided to reschedule your pods. Arroyo is built to run in modern, elastic cloud environments, from simple container runtimes like Fargate to large, distributed deployments on the Kubernetes logo Kubernetes.
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    Materialize

    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
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    TIBCO Streaming
    TIBCO Streaming is a real-time analytics platform designed to process and analyze high-velocity data streams, enabling organizations to make immediate, data-driven decisions. It offers a low-code development environment through StreamBase Studio, allowing users to build complex event processing applications with minimal coding. It supports over 150 connectors, including APIs, Apache Kafka, MQTT, RabbitMQ, and databases like MySQL and JDBC, facilitating seamless integration with various data sources. TIBCO Streaming incorporates dynamic learning operators, enabling adaptive machine learning models that provide contextual insights and automate decision-making processes. It also features real-time business intelligence capabilities, allowing users to visualize live data alongside historical information for comprehensive analysis. It is cloud-ready, supporting deployments on AWS, Azure, GCP, and on-premises environments.
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    Memurai

    Memurai

    Memurai

    Redis for Windows alternative, In-Memory Datastore Ready for the most demanding production workloads. Free for development and testing. Fully Redis-compatible. The core of Memurai is based on the Redis source code, ported to run natively on Windows. Memurai reliably supports all the features that make Redis the most popular NoSQL data store, including LRU eviction, persistence, replication, transactions, LUA scripting, high-availability, pub/sub, cluster, modules, and streams. A lot of attention has been put into ensuring full compatibility, including with the myriad of libraries and tools already available for Redis. You can even replicate data between Memurai and Redis, or use both within the same cluster! Seamless integration with Windows infrastructure and workflows. Whether it's used for development or production, Memurai seamlessly integrates with Windows best practices, tools and workflows. Engineering teams with an existing investments in the Windows infrastructure will be
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    TIBCO Platform

    TIBCO Platform

    Cloud Software Group

    TIBCO delivers industrial-strength solutions that meet your performance, throughput, reliability, and scalability needs while offering a wide range of technology and deployment options to deliver real-time data where it’s needed most. The TIBCO Platform will bring together an evolving set of your TIBCO solutions wherever they are hosted—in the cloud, on-premises, and at the edge—into a single, unified experience so that you can more easily manage and monitor them. TIBCO helps build solutions that are essential to the success of the world’s largest enterprises.
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    InfinyOn Cloud
    InfinyOn has architected a programmable continuous intelligence platform for data in motion. Unlike other event streaming platforms that were built on Java, Infinyon Cloud is built on Rust and delivers industry leading scale and security for real-time applications. Ready to use programmable connectors that shape data events in real-time. Provision intelligent analytics pipelines that refine, protect, and correlate events in real-time. Attach programmable connectors to dispatch events and notify stakeholders. Each connector is either a source, which imports data, or a sink, which exports data. Connectors may be deployed in one of two ways: as a Managed Connector, in which the Fluvio cluster provisions and manages the connector; or as a Local Connector, in which you manually launch the connector as a docker container where you want it. Additionally, connectors conceptually have four stages, where each stage has distinct responsibilities.