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DistributedLog vs StreamSets

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DistributedLog
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StreamSets
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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
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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?
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    What tools integrate with DistributedLog?
    What tools integrate with StreamSets?
      No integrations found

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      What are some alternatives to DistributedLog and StreamSets?
      Kafka
      Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
      MySQL
      The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
      PostgreSQL
      PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
      MongoDB
      MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
      Redis
      Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
      See all alternatives

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