Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Apache and others in Streaming Analytics.
| Product | Mindshare (%) |
|---|---|
| Apache Kafka | 4.1% |
| Striim | 1.5% |
| Other | 94.4% |
| Company Size | Count |
|---|---|
| Small Business | 32 |
| Midsize Enterprise | 18 |
| Large Enterprise | 50 |
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.
The Striim platform makes it easy to ingest, process, and deliver real-time data across diverse environments in the cloud or on-premise, helping you rapidly adopt a modern data architecture. With Striim you can build streaming data pipelines to cloud environments - such as Microsoft Azure, Amazon AWS, and Google Cloud Platform - as well as Kafka, Hadoop, NoSQL and relational databases (on-premises or in the cloud) with reliability, security, and scalability.
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