Best Streaming Analytics Platforms for Cloud

Cumulocity offers an enterprise-grade AIoT platform that connects & manages assets efficiently, transforms raw device data into AI-ready data, and orchestrates innovation from cloud to edge, combined with a team of experts and a large ecosystem of device, technology, and implementation partners to achieve lasting customer success. Cumulocity is the preferred choice for industrial equipment makers to develop high-value digital services and is trusted by leading companies worldwide as their partner, knowing they have access to the software and services needed to power their smart connected products in manufacturing, fleet management, consumer electronics, and more.

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.

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.

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.

Kapacitor is a native data processing engine for InfluxDB 1.x and is an integrated component in the InfluxDB 2.0 platform. Kapacitor can process both stream and batch data from InfluxDB, acting on this data in real-time via its programming language TICKscript. Today’s modern applications require more than just dashboarding and operator alerts—they need the ability to trigger actions. Kapacitor’s alerting system follows a publish-subscribe design pattern. Alerts are published to topics and handlers subscribe to a topic. This pub/sub model and the ability for these to call User Defined Functions make Kapacitor very flexible to act as the control plane in your environment, performing tasks like auto-scaling, stock reordering, and IoT device control. Kapacitor provides a simple plugin architecture, or interface, that allows it to integrate with any anomaly detection engine.

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.

eRAG (enterprise RAG) combines the power of real-time operational data with GPT’s fantastic user experience: Chat spontaneously and get immediate answers grounded in a unique understanding of your operational data. With its sophisticated semantic reasoning capabilities, eRAG ensures you get accurate, consistent answers. It answers complex, cross-system questions instantly, supports decisions with suggestions, challenges, and next steps. eRAG connects your business data with external events, so that you can weigh the effect of new tax legislation or weather disruptions on your operations. eRAG combines all your operational data sources so you can get a full, unified picture of your business, offering measurable revenue and efficiency outcomes. Through a self-serve UI, IT teams can connect SQL-based databases like Oracle, PostgreSQL, SAP and other systems in just a few clicks. And you can get up and running in 2–3 weeks - no data prep needed.

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.

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.

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.