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DistributedLog

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DistributedLog vs StreamSets: What are the differences?

Developers describe DistributedLog as "High-performance replicated log service, by Twitter". DistributedLog (DL) is a high-performance, replicated log service, offering durability, replication and strong consistency as essentials for building reliable distributed systems. On the other hand, StreamSets is detailed as "Where DevOps Meets Data Integration". The industry's first data operations platform for full life-cycle management of data in motion.

DistributedLog belongs to "Message Queue" category of the tech stack, while StreamSets can be primarily classified under "Data Science Tools".

Some of the features offered by DistributedLog are:

  • High Performance
  • Durable and Consistent
  • Efficient Fan-in and Fan-out

On the other hand, StreamSets provides the following key features:

  • Build Batch & Streaming Pipelines in Hours
  • Map and Monitor Runtime Performance
  • Protect Sensitive Data as it Arrives

DistributedLog is an open source tool with 2.25K GitHub stars and 283 GitHub forks. Here's a link to DistributedLog's open source repository on GitHub.

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Cons of DistributedLog
Cons of StreamSets
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      No user community
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    What is DistributedLog?

    DistributedLog (DL) is a high-performance, replicated log service, offering durability, replication and strong consistency as essentials for building reliable distributed systems.

    What is StreamSets?

    An end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps.

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    What companies use DistributedLog?
    What companies use StreamSets?
    See which teams inside your own company are using DistributedLog or StreamSets.
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    What tools integrate with DistributedLog?
    What tools integrate with StreamSets?
      No integrations found

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