Software Alternatives & Reviews


Confluent offers a real-time data platform built around Apache Kafka.

Confluent Alternatives

The best Confluent alternatives based on verified products, community votes, reviews and other factors.
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  1. 40

    Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

  2. 25

    Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

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  4. 19

    Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.

  5. 17

    Seamless two-way sync between your CRM, marketing apps and Google in no time

  6. 17

    Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

  7. 21

    Azure Stream Analytics offers real-time stream processing in the cloud.

  8. 21

    Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

  9. 16

    Cloud Pub/Sub is a flexible, reliable, real-time messaging service for independent applications to publish & subscribe to asynchronous events.

  10. 14

    MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.

  11. 14

    TIBCO Spotfire is a Business Intelligence (BI) solution that provides users with executive dashboards, data visualization, data analytics and KPIs push to mobile devices.

  12. 15

    Amazon Elasticsearch Service is a managed service that makes it easy to deploy, operate, and scale Elasticsearch in the AWS Cloud.

  13. 16

    Easily visualize data pushed into Elasticsearch from Logstash, es-hadoop or 3rd party technologies...

  14. 17

    Arcadia Enterprise is the ultimate native BI for data lakes with real-time streaming visualizations, all without adding hardware or moving data.

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Author: | Publisher: SaaSHub
Categories: Stream Processing, Data Management, Big Data


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