# trinodb/trino

Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)

Repository: https://github.com/trinodb/trino
Canonical: https://ross.abutalabs.com/products/trino
Homepage: https://trino.io
Language: Java
License: Apache-2.0
License Family: permissive
Topics: java, presto, hive, hadoop, big-data, sql, prestodb, database, databases, distributed-systems, distributed-database, data-science, datalake, jdbc, query-engine, trino, analytics, delta-lake, iceberg
Last push: 2026-08-26T20:27:13+00:00

## Health v2 (maintenance only)
Score: 93/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 81, longevity 100
- inputs: {"age_days": 2783, "days_push": 7, "days_rel": 47, "gap_med": 45.0, "n_releases_24m": 7}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 13183, forks 3749 (observed 2026-08-28T04:11:02.471161+00:00)

## What it is
Trino is a fast, distributed ANSI SQL query engine for big data analytics, formerly known as PrestoSQL. It queries data in place across diverse sources such as data lakes (Hive, Iceberg, Delta Lake), object storage, and relational databases, with support for query federation and BI tool integration.

## Use cases
- run interactive SQL analytics against data lakes on S3 or Hadoop
- federate queries joining data from MySQL, Kafka, Cassandra, and object storage in one SQL statement
- connect BI tools like Tableau, Power BI, or Superset to a fast SQL engine
- query Iceberg and Delta Lake lakehouse tables at scale
- execute large multi-hour batch queries and sub-second high-volume app queries
- explore exabyte-scale data warehouses without copying data

## When to choose
- you need low-latency, distributed SQL analytics over heterogeneous data sources
- you want in-place querying and federation without ETL data copies
- you need an ANSI SQL engine that integrates with standard BI tools and JDBC clients

## When to avoid
- you need a transactional OLTP database for writes and small point lookups
- you want a small single-node embedded database for an application
- your workload is simple analytics on one small dataset where a lightweight engine suffices

## Facets
- artifact type: application
- maturity: stable
- function: database, search-engine, analytics, etl
- domain: big-data, databases, data-science, analytics
- platform: jvm, cloud, self-hosted
- tags: sql-query-engine, distributed-systems, data-lake, lakehouse, query-federation, presto, jdbc, iceberg, delta-lake, sql, data-engineering, linux, macos, docker

## Member repositories
- trinodb/trino (main) score 93

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:02.471161+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 2026-08-29T17:13:27.588973+00:00, confidence not recorded.
  - readme: https://github.com/trinodb/trino (fetched 2026-08-28T04:11:02.471161+00:00, sha 6dbe5fbb7682)
  - homepage: https://trino.io (fetched 2026-08-29T08:08:46.351093+00:00, sha f9d3c577842e)
  - site_page: https://trino.io/docs/current (fetched 2026-08-29T08:08:46.360702+00:00, sha 84e6b0c34f8e)
  - site_page: https://trino.io/docs/current/develop.html (fetched 2026-08-29T08:08:46.362420+00:00, sha 391341025329)
  - site_page: https://trino.io/trino-the-definitive-guide (fetched 2026-08-29T08:08:46.363942+00:00, sha 4d8aa82dec32)
- Data as of 2026-08-30T08:39:29.467469+00:00.