Best Streaming Analytics Platforms
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Compare the Top Streaming Analytics Platforms as of October 2025
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What are Streaming Analytics Platforms?
Streaming analytics platforms are software solutions that enable real-time processing and analysis of data as it is generated or streamed from various sources such as IoT devices, sensors, social media, and transactional systems. These platforms allow businesses to gain immediate insights from continuous data streams, enabling them to make faster decisions, detect anomalies, and optimize operations in real-time. Key features of streaming analytics platforms include data ingestion, real-time event processing, pattern recognition, and advanced analytics like predictive modeling and machine learning integration. They are commonly used in applications such as fraud detection, customer behavior analysis, network monitoring, and supply chain optimization. Compare and read user reviews of the best Streaming Analytics platforms currently available using the table below. This list is updated regularly.
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1
Gathr.ai
Gathr.ai
Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500Starting Price: $0.25/credit -
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IBM Streams
IBM
IBM Streams evaluates a broad range of streaming data — unstructured text, video, audio, geospatial and sensor — helping organizations spot opportunities and risks and make decisions in real-time. Make sense of your data, turning fast-moving volumes and varieties into insight with IBM® Streams. Streams evaluate a broad range of streaming data — unstructured text, video, audio, geospatial and sensor — helping organizations spot opportunities and risks as they happen. Combine Streams with other IBM Cloud Pak® for Data capabilities, built on an open, extensible architecture. Help enable data scientists to collaboratively build models to apply to stream flows, plus, analyze massive amounts of data in real-time. Acting upon your data and deriving true value is easier than ever. -
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IBM StreamSets
IBM
IBM® StreamSets enables users to create and manage smart streaming data pipelines through an intuitive graphical interface, facilitating seamless data integration across hybrid and multicloud environments. This is why leading global companies rely on IBM StreamSets to support millions of data pipelines for modern analytics, intelligent applications and hybrid integration. Decrease data staleness and enable real-time data at scale—handling millions of records of data, across thousands of pipelines within seconds. Insulate data pipelines from change and unexpected shifts with drag-and-drop, prebuilt processors designed to automatically identify and adapt to data drift. Create streaming pipelines to ingest structured, semistructured or unstructured data and deliver it to a wide range of destinations.Starting Price: $1000 per month -
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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. -
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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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GigaSpaces
GigaSpaces
Smart DIH is an operational data hub that powers real-time modern applications. It unleashes the power of customers’ data by transforming data silos into assets, turning organizations into data-driven enterprises. Smart DIH consolidates data from multiple heterogeneous systems into a highly performant data layer. Low code tools empower data professionals to deliver data microservices in hours, shortening developing cycles and ensuring data consistency across all digital channels. XAP Skyline is a cloud-native, in memory data grid (IMDG) and developer framework designed for mission critical, cloud-native apps. XAP Skyline delivers maximal throughput, microsecond latency and scale, while maintaining transactional consistency. It provides extreme performance, significantly reducing data access time, which is crucial for real-time decisioning, and transactional applications. XAP Skyline is used in financial services, retail, and other industries where speed and scalability are critical. -
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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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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. -
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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. -
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SAS Event Stream Processing
SAS Institute
Streaming data from operations, transactions, sensors and IoT devices is valuable – when it's well-understood. Event stream processing from SAS includes streaming data quality and analytics – and a vast array of SAS and open source machine learning and high-frequency analytics for connecting, deciphering, cleansing and understanding streaming data – in one solution. No matter how fast your data moves, how much data you have, or how many data sources you’re pulling from, it’s all under your control via a single, intuitive interface. You can define patterns and address scenarios from all aspects of your business, giving you the power to stay agile and tackle issues as they arise. -
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Kinetica
Kinetica
A scalable cloud database for real-time analysis on large and streaming datasets. Kinetica is designed to harness modern vectorized processors to be orders of magnitude faster and more efficient for real-time spatial and temporal workloads. Track and gain intelligence from billions of moving objects in real-time. Vectorization unlocks new levels of performance for analytics on spatial and time series data at scale. Ingest and query at the same time to act on real-time events. Kinetica's lockless architecture and distributed ingestion ensures data is available to query as soon as it lands. Vectorized processing enables you to do more with less. More power allows for simpler data structures, which lead to lower storage costs, more flexibility and less time engineering your data. Vectorized processing opens the door to amazingly fast analytics and detailed visualization of moving objects at scale. -
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Cumulocity IoT
Software AG
Cumulocity IoT is the #1 low-code, self-service IoT platform—the only one that comes pre-integrated with the tools you need for fast results: device connectivity and management, application enablement and integration, as well as streaming and predictive analytics. Free your business from proprietary technology stacks. Because you’ll be using the only completely open IoT platform, you can connect any “thing” today and tomorrow. Bring your own hardware and tools, and pick the components that best fit. Get up and running on the IoT in minutes. Connect a device and view its data. Create a real-time interactive dashboard. Define rules to monitor and act on events. Do all of this without calling on IT or writing any code! Easily integrate new IoT data with the core enterprise systems, applications and processes that have run your business for years—again, without coding—for a fluid flow of data. You’ll have more context to make better decisions. -
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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. -
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Informatica Data Engineering Streaming
Informatica
AI-powered Informatica Data Engineering Streaming enables data engineers to ingest, process, and analyze real-time streaming data for actionable insights. Advanced serverless deployment option with integrated metering dashboard cuts admin overhead. Rapidly build intelligent data pipelines with CLAIRE®-powered automation, including automatic change data capture (CDC). Ingest thousands of databases and millions of files, and streaming events. Efficiently ingest databases, files, and streaming data for real-time data replication and streaming analytics. Find and inventory all data assets throughout your organization. Intelligently discover and prepare trusted data for advanced analytics and AI/ML projects. -
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Azure Stream Analytics
Microsoft
Discover Azure Stream Analytics, the easy-to-use, real-time analytics service that is designed for mission-critical workloads. Build an end-to-end serverless streaming pipeline with just a few clicks. Go from zero to production in minutes using SQL—easily extensible with custom code and built-in machine learning capabilities for more advanced scenarios. Run your most demanding workloads with the confidence of a financially backed SLA. -
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Esper Enterprise Edition
EsperTech Inc.
Esper Enterprise Edition is a distributable platform for linear and elastic horizontal scalability and fault-tolerant event processing. EPL editor and debugger; Hot deployment; Detailed metric and memory use reporting with break-down and summary per EPL. Data Push for multi-tier CEP-to-Browser delivery; Management of Logical and Physical Subscribers and Subscriptions. Web-based user interface for managing all aspects of multiple distributed engine instances with JavaScript and HTML 5. Composable, configurable and interactive displays of distributed event streams or series; Charts, Gauges, Timelines, Grids. JDBC-compliant client and server endpoints for interoperability. Esper Enterprise Edition is a closed-source commercial product by EsperTech. The source code is made available to support customers only. Esper Enterprise Edition is a distributable platform for linear and elastic horizontal scalability and fault-tolerant event processing. -
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Evam's Continuous Intelligence Platform combines multiple products for processing and visualizing real-time data. It runs real-time machine learning models on streaming data, while enriching the real-time data with a smart in-memory caching mechanism. EVAM empowers telecommunications, financial services, retail, transportation and travel companies to maximize their business value. Through continuous intelligence platform with machine learning capabilities. EVAM processes real-time data and designs and orchestrates customer journeys visually with advanced analytical models, machine learning, and artificial intelligence algorithms. EVAM enables enterprises to engage their customers using their data across all channels, including legacy ones, in real-time. Collect billions of events and process them in real-time. Understand each customer's needs and attract, engage, and retain them more effectively.
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Oracle Stream Analytics
Oracle
Oracle Stream Analytics allows users to process and analyze large scale real-time information by using sophisticated correlation patterns, enrichment, and machine learning. It offers real-time actionable business insight on streaming data and automates action to drive today’s agile businesses. Visual GEOProcessing with GEOFence relationship spatial analytics. New Expressive Patterns Library, including Spatial, Statistical, General industry and Anomaly detection, streaming machine learning. Abstracted visual façade to interrogate live real time streaming data and perform intuitive in-memory real time business analytics. -
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TreasuryPay
TreasuryPay
Instant™ Enterprise Data and Intelligence. Visibility into all transaction data, as it is happening, wherever it is happening worldwide. With just one network connection, organizations receive worldwide Accounting, Liquidity Management, FX, Marketing, and Supply Chain information — delivered in a single managed solution to empower enterprise intelligence. The TreasuryPay product set streams your global receivables information, delivering instant accountancy and cognitive services. It is, quite simply, the most advanced intelligence and insights platform currently available to global organizations. Instantly provide your organization with enriched information for your entire global enterprise. The change is easy. The Return on Investment, remarkable. Actionable intelligence and real-time global accountancy are now available at your fingertips with TreasuryPay Instant™. -
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VIA provides visibility across data and organizational silos enabling operational effectiveness for many industries. Your team will isolate problems faster, automate response when possible and prevent the problems most likely to impact service and your customers’ experience. Enabled by its action-oriented analytic value chain and customer-centric approach, VIA reveals and automates what to do, then prioritizes based on customer impact so you can take decisions and act with confidence to improve business outcomes. VIA Solution Templates accelerate deployment and adaptation of the Platform to meet your unique business requirements.
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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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