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Dev tools · alternatives · 2026

24 alternatives to Software Engineering Daily - The History of Hadoop

A look back at the framework that defines "big data"

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Software Engineering Daily - The History of Hadoop launched in 2016; newer entries below may have overtaken it.

  1. 1

    Hadoop, Cloudera, Open Source Software & Big Data

    2015 · its alternatives →

  2. 2

    Everything you need to know about Big Data

    2016 · its alternatives →

  3. 3

    Hadoop is behind just about everything you touch on the web

    2016 · its alternatives →

  4. 4SA
  5. 5CA
  6. 6IM

    2017 · xyz.insightdataengineering.com · its alternatives →

  7. 7CD
  8. 8DP
  9. 9
    DataFox▲80

    Harness big data to make smarter decisions.

    2014 · its alternatives →

  10. 10

    The data community's workbench

    2018 · its alternatives →

  11. 11

    Advanced, cloud-based research collaboration

    2017 · its alternatives →

  12. 12
    Dremio▲67

    The missing link in modern data

    2017 · its alternatives →

  13. 13HI

    2013 · datanitro.com · its alternatives →

  14. 14TA
  15. 15
  16. 16PA
  17. 17
    Fathym▲63

    The data application orchestration and development framework

    2020 · its alternatives →

  18. 18DM
  19. 19

    The scalable blockchain database.

    2016 · its alternatives →

  20. 20
    BigML▲64

    Machine learning as a service - build predictive apps

    2014 · its alternatives →

  21. 21

    It's not what you say, it's how you say it

    2016 · its alternatives →

  22. 22

    A grid library for instant big data processing

    2022 · its alternatives →

  23. 23

    A fast, fully managed, scalable NoSQL database service

    2015 · its alternatives →

  24. 24OS

    Hey HN, I am the founder of Tensorlake. Prototyping LLM applications have become a lot easier, building decision making LLM applications that work on constantly updating data is still very challenging in production settings. The systems engineering problems that we have seen people face are - 1. Reliably process ingested content in real time if the application is sensitive to freshness of information. 2. Being able to bring in any kind of model, and run different parts of the pipeline on GPUs and CPUs. 3. Fault Tolerance to ingestion spike, compute infrastructure failure. 4. Scaling compute,…

    2024 · getindexify.ai · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →