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10 Best Stream Analytics Tools in 2022.

Apache Kafka is a distributed event store and stream-processing platform. It is an open-source system developed by the Apache Software Foundation written in Java and Scala.

Apache Kafka

Apache Spark is an open-source unified analytics engine for large-scale data processing. It provides an interface for programming clusters with implicit data parallelism & fault tolerance.

Apache Spark

Amazon Kinesis makes it easy to collect, process, and analyze real-time streaming data such as video, audio, application logs, website clickstreams, and IoT telemetry.

Amazon Kinesis

Amazon Kinesis makes it easy to collect, process, and analyze real-time streaming data such as video, audio, application logs, website clickstreams, and IoT telemetry.

Google Cloud Dataflow

RapidMiner is another cloud-based software that enables you to build a complete end-to-end streaming data analytics platform. It’s an open-source application & incorporates various features.

RapidMiner

StreamSets DataOps Platform empowers your whole team, from highly skilled data engineers to visual ETL developers, to do powerful data engineering work.

StreamSets DataOps

Oracle Stream Analytics lets users process and analyze large-scale real-time information by using sophisticated correlation patterns, enrichment, and machine learning.

Oracle

Memgraph is a real-time graph streaming platform that allows you to explore data locally and on a cloud platform.

Memgraph

Lenses.io delivers a developer workspace for building & operating real-time applications on any Apache Kafka. Enabling teams to monitor, investigate, secure & deploy on their data platform.

Lenses.io

The effectiveness of StreamSQL for real-time information computation in big data is dependent on its simplification. StreamSQL’s simplification makes it appropriate for non-developers as well

StreamSQL

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