ytsaurus/ytsaurus
YTsaurus is a scalable and fault-tolerant open-source big data platform. observed · 2026-08-28
Health v2 · maintenance only
94/100
- Activity 99
- Release rhythm 86
- Longevity 97
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 4
- age_days: 1367
- days_rel: 19
- days_push: 7
- n_releases_24m: 102
Adoption not part of the score
2200 stars · 218 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
YTsaurus is an open-source, fault-tolerant big data platform combining distributed storage, MapReduce processing, a SQL query engine, and a NoSQL key-value store. It integrates ClickHouse (CHYT) for fast analytics and Apache Spark (SPYT) for ETL, and scales to exabytes of data and millions of CPU cores.
Use cases
- run MapReduce batch jobs over large datasets
- run ad hoc SQL analytics without exporting data to an external OLAP system
- store and query data with a low-latency transactional key-value store
- build ETL pipelines with Apache Spark or SQL
- manage GPU clusters for training large machine learning models
- store transactional metadata for distributed systems
- deploy a multi-tenant big data platform on Kubernetes
When to choose
- you need a scalable, fault-tolerant platform combining storage, batch processing, and analytics in one system
- you want multi-tenant big data infrastructure serving many users on shared hardware
- you need exabyte-scale storage with no single point of failure
- you want ClickHouse-style SQL analytics directly on your data lake
- you need a transactional key-value store for OLTP workloads alongside batch processing
When to avoid
- you only need a simple single-node database or analytics engine
- you want a fully managed cloud service without operating your own cluster
- your workloads are small enough for Postgres, ClickHouse, or Spark alone
- you need a lightweight embedded or edge deployment
Facets
service · maturity active
database search-engine etl streaming scheduling caching big-data databases microservices analytics self-hosted cloud big-data mapreduce distributed-file-system nosql olap sql-query-engine clickhouse apache-spark key-value-store data-lakehouse data-engineering linux docker kubernetes
4 sources
- readme: https://github.com/ytsaurus/ytsaurus · fetched 2026-08-28 · 8bcfe4f072bf
- homepage: https://ytsaurus.tech · fetched 2026-08-29 · 7e1c3cf39411
- site_page: https://ytsaurus.tech/docs/en · fetched 2026-08-29 · e9a813b24cd6
- site_page: https://ytsaurus.tech/docs/en/overview/try-yt · fetched 2026-08-29 · 8c58b14cdfe4
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| ytsaurus/ytsaurus | main | 94 |
For agents
markdown · JSON · MCP: product_card(name="ytsaurus/ytsaurus")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem