Distributed MapReduce framework in Go

In plain words

This is a distributed MapReduce framework written in Go, designed for developers who need to process large datasets across multiple machines. It implements the MapReduce programming model, allowing users to write parallel processing jobs in Go. The framework was launched in 2015 and is available on GitHub, making it suitable for teams building scalable data processing systems.

written from the facts on this page · September 2026

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  Go Micro – A distributed systems development framework2020 · go-micro.dev · ▲115

  I can't tell if HN is the right kind of place for this stuff anymore since people are so advanced in their use but I thought it was interesting to leverage my existing Go microservices framework and turn it into the core of what would provide tools for an agent cli or whatever beyond that. Extensibility is key. Thought I'd share and get a conversation going.

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  Capillaries: Distributed data processing with Go and Cassandra2023 · capillaries.io · ▲70

  I started thinking about this approach after working on a large-scale project for a major financial company where our group developed a distributed in-house data processing solution. On a regular basis, it ingested a few gigabytes of financial data and, within a tight SLA time limit, produced a lot of enriched/aggregated/validated data for a number of customers. Sometimes, source data had errors, so operators with domain knowledge had to verify data validity at some checkpoints, immediately make corrections, and re-run parts of the workflow manually. The solution involved complex…

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  A Database Written in Golang2025 · github.com · ▲277

  Recently created a minimal persistent relational database in Go. Main focus was on implementing & understanding working the of database, storage management & transaction handling. Use of B+ Tree for storage engine(support for indexing), managing a Free List (for reusing nodes), Support for transactions, Concurrent Reads. Still have many things to add & fix like query processing being one of the main & fixing some bugs Repo link - https://github.com/Sahilb315/AtomixDB Would love to hear your thoughts

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