Best Real-Time Data Streaming Tools
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Compare the Top Real-Time Data Streaming Tools as of September 2026
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What are Real-Time Data Streaming Tools?
Real-time data streaming tools enable organizations, big data and machine learning professionals, and data scientists to stream data in real time, and build data models when new data is created or ingested. Compare and read user reviews of the best Real-Time Data Streaming tools currently available using the table below. This list is updated regularly.
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1
Databricks
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
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Geckoboard
Geckoboard
Build and share real-time business dashboards without the hassle. Geckoboard integrates with over 80 tools to help you pull in your data and get a professional-looking dashboard in front of others in a matter of minutes. Create dashboards directly in your browser with a straightforward, drag-and-drop interface, and bring important numbers, metrics and KPIs out of lifeless reports. Geckoboard makes your key data more engaging for everyone, with visualizations that anyone can understand at a glance, and that update automatically to always stay up-to-date. When you're ready, share your dashboard with a link, invite your teammates, schedule email and Slack updates to go out automatically, or display it proudly in the office on a big screen or TV.Starting Price: $35 per month -
3
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.Starting Price: Free -
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PubSub+ Platform
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. -
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Decodable
Decodable
No more low level code and stitching together complex systems. Build and deploy pipelines in minutes with SQL. A data engineering service that makes it easy for developers and data engineers to build and deploy real-time data pipelines for data-driven applications. Pre-built connectors for messaging systems, storage systems, and database engines make it easy to connect and discover available data. For each connection you make, you get a stream to or from the system. With Decodable you can build your pipelines with SQL. Pipelines use streams to send data to, or receive data from, your connections. You can also use streams to connect pipelines together to handle the most complex processing tasks. Observe your pipelines to ensure data keeps flowing. Create curated streams for other teams. Define retention policies on streams to avoid data loss during external system failures. Real-time health and performance metrics let you know everything’s working.Starting Price: $0.20 per task per hour -
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Tinybird
Tinybird
Query and shape your data using Pipes, a new way to chain SQL queries inspired by Python Notebooks. Designed to reduce complexity without sacrificing performance. By splitting your query in different nodes you simplify development and maintenance. Activate your production-ready API endpoints with one click. Transformations occur on-the-fly so you will always work with the latest data. Share access securely to your data in one click and get fast and consistent results. Apart from providing monitoring tools, Tinybird scales linearly: don't worry about traffic spikes. Imagine if you could turn, in a matter of minutes, any Data Stream or CSV file into a fully secured real-time analytics API endpoint. We believe in high-frequency decision-making for all organizations in all industries including retail, manufacturing, telecommunications, government, advertising, entertainment, healthcare, and financial services.Starting Price: $0.07 per processed GB -
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Yandex Data Streams
Yandex
Simplifies data exchange between components in microservice architectures. When used as a transport for microservices, it simplifies integration, increases reliability, and improves scaling. Read and write data in near real-time. Set data throughput and storage times to meet your needs. Enjoy granular configuration of the resources for processing data streams, from small streams of 100 KB/s to streams of 100 MB/s. Deliver a single stream to multiple targets with different retention policies using Yandex Data Transfer. Data is automatically replicated across multiple geographically distributed availability zones. Once created, you can manage data streams centrally in the management console or using the API. Yandex Data Streams can continuously collect data from sources like website browsing histories, application and system logs, and social media feeds. Yandex Data Streams is capable of continuously collecting data from sources such as website browsing histories, application logs, etc.Starting Price: $0.086400 per GB -
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Timeplus
Timeplus
Timeplus is a simple, powerful, and cost-efficient stream processing platform. All in a single binary, easily deployed anywhere. We help data teams process streaming and historical data quickly and intuitively, in organizations of all sizes and industries. Lightweight, single binary, without dependencies. End-to-end analytic streaming and historical functionalities. 1/10 the cost of similar open source frameworks. Turn real-time market and transaction data into real-time insights. Leverage append-only streams and key-value streams to monitor financial data. Implement real-time feature pipelines using Timeplus. One platform for all infrastructure logs, metrics, and traces, the three pillars supporting observability. In Timeplus, we support a wide range of data sources in our web console UI. You can also push data via REST API, or create external streams without copying data into Timeplus.Starting Price: $199 per month -
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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 -
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Thousands of customers use Amazon Managed Service for Apache Flink to run stream processing applications. With Amazon Managed Service for Apache Flink, you can transform and analyze streaming data in real-time using Apache Flink and integrate applications with other AWS services. There are no servers and clusters to manage, and there is no computing and storage infrastructure to set up. You pay only for the resources you use. Build and run Apache Flink applications, without setting up infrastructure and managing resources and clusters. Process gigabytes of data per second with subsecond latencies and respond to events in real-time. Deploy highly available and durable applications with Multi-AZ deployments and APIs for application lifecycle management. Develop applications that transform and deliver data to Amazon Simple Storage Service (Amazon S3), Amazon OpenSearch Service, and more.Starting Price: $0.11 per hour
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Amazon Data Firehose
Amazon
Easily capture, transform, and load streaming data. Create a delivery stream, select your destination, and start streaming real-time data with just a few clicks. Automatically provision and scale compute, memory, and network resources without ongoing administration. Transform raw streaming data into formats like Apache Parquet, and dynamically partition streaming data without building your own processing pipelines. Amazon Data Firehose provides the easiest way to acquire, transform, and deliver data streams within seconds to data lakes, data warehouses, and analytics services. To use Amazon Data Firehose, you set up a stream with a source, destination, and required transformations. Amazon Data Firehose continuously processes the stream, automatically scales based on the amount of data available, and delivers it within seconds. Select the source for your data stream or write data using the Firehose Direct PUT API.Starting Price: $0.075 per month -
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Streamkap
Streamkap
Streamkap is a streaming data platform that makes streaming as easy as batch. Stream data from database (change data capturee) or event sources to your favorite database, data warehouse or data lake. Streamkap can be deployed as a SaaS or in a bring your own cloud (BYOC) deployment.Starting Price: $600 per month -
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Lightstreamer
Lightstreamer
Lightstreamer is an event broker optimized for the internet, ensuring seamless real-time data delivery across the web. Unlike traditional brokers, Lightstreamer automatically handles proxies, firewalls, disconnections, network congestion, and the general unpredictability of the internet. With its intelligent streaming feature, Lightstreamer guarantees real-time data transmission, always finding a way to deliver your data reliably and efficiently, ensuring robust last-mile messaging. Lightstreamer offers technology that is both mature and cutting-edge, continuously evolving to stay at the forefront of innovation. With a proven track record and years of field-tested performance, Lightstreamer ensures your data is delivered reliably and efficiently. Experience unparalleled reliability in any scenario with Lightstreamer.Starting Price: Free -
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SQLstream
Guavus, a Thales company
SQLstream ranks #1 for IoT stream processing & analytics (ABI Research). Used by Verizon, Walmart, Cisco, & Amazon, our technology powers applications across data centers, the cloud, & the edge. Thanks to sub-ms latency, SQLstream enables live dashboards, time-critical alerts, & real-time action. Smart cities can optimize traffic light timing or reroute ambulances & fire trucks. Security systems can shut down hackers & fraudsters right away. AI / ML models, trained by streaming sensor data, can predict equipment failures. With lightning performance, up to 13M rows / sec / CPU core, companies have drastically reduced their footprint & cost. Our efficient, in-memory processing permits operations at the edge that are otherwise impossible. Acquire, prepare, analyze, & act on data in any format from any source. Create pipelines in minutes not months with StreamLab, our interactive, low-code GUI dev environment. Export SQL scripts & deploy with the flexibility of Kubernetes. -
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Memgraph
Memgraph
Memgraph is a high-performance, in-memory graph database that powers real-time AI context. It serves as the graph engine for GraphRAG pipelines, AI memory systems, and agentic workflows - delivering sub-millisecond multi-hop traversals with full provenance for any system that needs structured, connected context alongside semantic search. The same architecture that makes Memgraph the context layer for AI also drives real-time graph analytics across fraud detection, network analysis, infrastructure monitoring, and other operational use cases where speed and connectivity matter. -
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Redpanda
Redpanda Data
Redpanda is pioneering the Agentic Data Plane (ADP) - a new category in AI infrastructure that makes it simple and secure to connect AI agents with enterprise data and systems. Built on a multi-modal data streaming engine, Redpanda empowers agentic applications that reason and act in real-time with speed, autonomy, and precision. Global leaders including Activision Blizzard, Cisco, Moody's, Texas Instruments, Vodafone and 2 of the top 5 banks in the U.S. rely on Redpanda to process hundreds of terabytes of data a day. Backed by premier venture investors Lightspeed, GV and Haystack VC, Redpanda is a diverse, people-first organization with teams distributed around the globe. -
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Astra Streaming
DataStax
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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3forge
3forge
Your enterprise's issues may be complex. That doesn't mean building the solution has to be. 3forge is the highly-flexible, low-code platform that empowers enterprise application development in record time. Reliability? Check. Scalability? That too. Deliverability? In record time. Even for the most complex work flows and data sets. With 3forge, you no longer have to choose. Data integration, virtualization, processing, visualization, and workflows all living in one place - solving the world's most complex real-time streaming data challenges. 3forge provides award-winning technology that enables developers to deploy mission-critical applications in record time. Experience the difference of real-time data and zero latency with 3forge's focus on data integration, virtualization, processing, and visualization. -
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TapData
TapData
CDC-based live data platform for heterogeneous database replication, real-time data integration, or building a real-time data warehouse. By using CDC to sync production line data stored in DB2 and Oracle to the modern database, TapData enabled an AI-augmented real-time dispatch software to optimize the semiconductor production line process. The real-time data made instant decision-making in the RTD software a possibility, leading to faster turnaround times and improved yield. As one of the largest telcos, customer has many regional systems that cater to the local customers. By syncing and aggregating data from various sources and locations into a centralized data store, customers were able to build an order center where the collective orders from many applications can now be aggregated. TapData seamlessly integrates inventory data from 500+ stores, providing real-time insights into stock levels and customer preferences, enhancing supply chain efficiency. -
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Enrich.sh
Enrich.sh
Enrich.sh is a high-performance data enrichment infrastructure platform as a service designed to power real-time data workflows at scale with minimal latency and high throughput. It enables businesses and developers to enrich, process, and transform large volumes of data (500+ requests per second) with sub-millisecond response times, making it suitable for performance-sensitive and edge-oriented applications. It is built for big data at the edge, offering a backend service that handles enrichment workloads efficiently without the need for heavy operational overhead, allowing teams to focus on core product development rather than infrastructure management. Enrich.sh provides robust APIs that let users ingest, augment, and serve enriched data quickly, supporting complex enrichment strategies and rapid data pipelines for analytical or transactional use cases.Starting Price: $49 per month -
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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. -
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Apache NiFi
Apache Software Foundation
An easy to use, powerful, and reliable system to process and distribute data. Apache NiFi supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic. Some of the high-level capabilities and objectives of Apache NiFi include web-based user interface, offering a seamless experience between design, control, feedback, and monitoring. Highly configurable, loss tolerant, low latency, high throughput, and dynamic prioritization. Flow can be modified at runtime, back pressure, data provenance, track dataflow from beginning to end, designed for extension. Build your own processors and more. Enables rapid development and effective testing. Secure, SSL, SSH, HTTPS, encrypted content, and much more. Multi-tenant authorization and internal authorization/policy management. NiFi is comprised of a number of web applications (web UI, web API, documentation, custom UI's, etc). So, you'll need to set up your mapping to the root path. -
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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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Baidu AI Cloud Stream Computing
Baidu AI Cloud
Baidu Stream Computing (BSC) provides real-time streaming data processing capacity with low delay, high throughput and high accuracy. It is fully compatible with Spark SQL; and can realize the logic data processing of complicated businesses through SQL statement, which is easy to use; provides users with full life cycle management for the streaming-oriented computing jobs. Integrate deeply with multiple storage products of Baidu AI Cloud as the upstream and downstream of stream computing, including Baidu Kafka, RDS, BOS, IOT Hub, Baidu ElasticSearch, TSDB, SCS and others. Provide a comprehensive job monitoring indicator, and the user can view the monitoring indicators of the job and set the alarm rules to protect the job. -
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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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Redpanda Agentic Data Plane
Redpanda Data
Redpanda is an enterprise data streaming platform designed to make AI agents safe, governed, and effective across all organizational data. Its Agentic Data Plane connects agents to data sources across cloud, on-prem, and hybrid environments without creating risk or chaos. Redpanda unifies live data streams and historical data into a single, queryable layer. Built-in governance ensures every agent action is authorized, logged, and auditable. The platform enables agents to retrieve exactly the data they need with full context. Redpanda records and replays all agent activity for transparency and debugging. It helps enterprises move from experimental AI to production-ready agentic systems. -
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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. -
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Hitachi Streaming Data Platform
Hitachi
The Hitachi Streaming Data Platform (SDP) is a real-time data processing system designed to analyze large volumes of time-sequenced data as it is generated. By leveraging in-memory and incremental computational processing, SDP enables swift analysis without the delays associated with traditional stored data processing. Users can define summary analysis scenarios using Continuous Query Language (CQL), similar to SQL, allowing for flexible and programmable data analysis without the need for custom applications. The platform's architecture comprises components such as development servers, data-transfer servers, data-analysis servers, and dashboard servers, facilitating scalable and efficient data processing workflows. SDP's modular design supports various data input and output formats, including text files and HTTP packets, and integrates with visualization tools like RTView for real-time monitoring. -
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Cloudera DataFlow
Cloudera
Cloudera DataFlow for the Public Cloud (CDF-PC) is a cloud-native universal data distribution service powered by Apache NiFi that lets developers connect to any data source anywhere with any structure, process it, and deliver to any destination. CDF-PC offers a flow-based low-code development paradigm that aligns best with how developers design, develop, and test data distribution pipelines. With over 400+ connectors and processors across the ecosystem of hybrid cloud services—including data lakes, lakehouses, cloud warehouses, and on-premises sources—CDF-PC provides indiscriminate data distribution. These data distribution flows can then be version-controlled into a catalog where operators can self-serve deployments to different runtimes.
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