# apache/hudi

Upserts, Deletes And Incremental Processing on Big Data.

Repository: https://github.com/apache/hudi
Canonical: https://ross.abutalabs.com/products/hudi
Homepage: https://hudi.apache.org/
Language: Java
License: Apache-2.0
License Family: permissive
Topics: hudi, apachehudi, datalake, bigdata, apachespark, incremental-processing, stream-processing, data-integration, apacheflink
Last push: 2026-08-26T23:40:35+00:00

## Health v2 (maintenance only)
Score: 91/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 75, longevity 100
- inputs: {"age_days": 3549, "days_push": 7, "days_rel": 86, "gap_med": 69, "n_releases_24m": 8}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6219, forks 2501 (observed 2026-08-28T04:09:40.658646+00:00)

## What it is
Apache Hudi is an open data lakehouse platform built on a high-performance open table format that brings database functionality like transactions, upserts, deletes, and indexing to data lakes. It supports incremental processing pipelines with low-latency analytics across engines such as Spark, Flink, Presto, and Trino.

## Use cases
- upsert and delete records in a data lake on S3
- build incremental streaming pipelines instead of batch jobs
- ingest database CDC changes into a lakehouse table
- query data lake tables with ACID guarantees from Spark or Trino
- time travel to query historical versions of a table
- deduplicate and merge high-throughput streaming data

## When to choose
- you need fast, mutable upserts/deletes on cloud object storage
- you want minute-level incremental processing over a data lake
- you need ACID transactions and concurrency control across multiple writers
- you use Spark or Flink and want an open table format with rich indexing

## When to avoid
- you only need append-only immutable data with simple reads
- your stack is non-JVM and you need full write support (hudi-rs is still maturing)
- you want a fully managed warehouse without operating table services like compaction and clustering

## Facets
- artifact type: library
- maturity: stable
- function: etl, streaming, database, data-science
- domain: big-data, databases, analytics
- platform: jvm, cloud, self-hosted
- tags: data-lakehouse, table-format, upserts, incremental-processing, acid-transactions, apache-spark, apache-flink, cdc, time-travel, open-table-format, data-engineering, docker

## Member repositories
- apache/hudi (main) score 91

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:40.658646+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:47:15.759082+00:00, confidence not recorded.
  - readme: https://github.com/apache/hudi (fetched 2026-08-28T04:09:40.658646+00:00, sha 7009412ae214)
  - homepage: https://hudi.apache.org/ (fetched 2026-08-29T08:43:48.330990+00:00, sha 7555aff3fef5)
  - site_page: https://hudi.apache.org/docs/overview (fetched 2026-08-29T08:43:48.340202+00:00, sha b18ddcd765f9)
  - site_page: https://hudi.apache.org/docs/quick-start-guide (fetched 2026-08-29T08:43:48.347357+00:00, sha d7d5f014159d)
  - site_page: https://hudi.apache.org/docs/indexes (fetched 2026-08-29T08:43:48.350018+00:00, sha 7d067d24398e)
  - site_page: https://hudi.apache.org/docs/concurrency_control (fetched 2026-08-29T08:43:48.352513+00:00, sha 953eb294c103)
  - site_page: https://hudi.apache.org/docs/sql_queries (fetched 2026-08-29T08:43:48.354806+00:00, sha b18fbd93b2c9)
  - site_page: https://hudi.apache.org/learn/faq (fetched 2026-08-29T08:43:48.342373+00:00, sha 39423159dae0)
  - site_page: https://hudi.apache.org/ecosystem (fetched 2026-08-29T08:43:48.344064+00:00, sha 201cc0caab05)
  - site_page: https://hudi.apache.org/releases/download (fetched 2026-08-29T08:43:48.345658+00:00, sha a1a46910c304)
- Data as of 2026-08-30T08:39:29.467469+00:00.