Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
| Product | Market Share (%) |
|---|---|
| Apache Kafka | 3.8% |
| Apache Flink | 12.3% |
| Databricks | 10.0% |
| Other | 73.9% |
| Product | Market Share (%) |
|---|---|
| IBM Event Streams | 2.0% |
| IBM MQ | 22.5% |
| ActiveMQ | 22.4% |
| Other | 53.1% |
| Company Size | Count |
|---|---|
| Small Business | 32 |
| Midsize Enterprise | 18 |
| Large Enterprise | 49 |
Apache Kafka is an open-source distributed streaming platform that serves as a central hub for handling real-time data streams. It allows efficient publishing, subscribing, and processing of data from various sources like applications, servers, and sensors.
Kafka's core benefits include high scalability for big data pipelines, fault tolerance ensuring continuous operation despite node failures, low latency for real-time applications, and decoupling of data producers from consumers.
Key features include topics for organizing data streams, producers for publishing data, consumers for subscribing to data, brokers for managing clusters, and connectors for easy integration with various data sources.
Large organizations use Kafka for real-time analytics, log aggregation, fraud detection, IoT data processing, and facilitating communication between microservices.
Built on open source Apache Kafka, IBM Event Streams is an event-streaming platform that helps you build smart applications that can react to events as they happen. IBM Event Streams is based on years of operational expertise IBM has gained from running Apache Kafka event streams for enterprises
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