# apache/drill

Apache Drill is a distributed MPP query layer for self describing data

Repository: https://github.com/apache/drill
Canonical: https://ross.abutalabs.com/products/apache-drill
Homepage: https://drill.apache.org/
Language: Java
License: Apache-2.0
License Family: permissive
Topics: java, big-data, drill, sql, hive, hadoop, jdbc, parquet
Last push: 2026-08-25T14:18:00+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 8, longevity 100
- inputs: {"age_days": 5110, "days_push": 8, "days_rel": 430, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2022, forks 990 (observed 2026-08-28T04:06:06.411626+00:00)

## What it is
Apache Drill is a distributed MPP (massively parallel processing) SQL query engine for self-describing data such as JSON, Parquet, and other schema-free formats. It queries NoSQL databases, Hadoop, and cloud storage systems directly with ANSI SQL, without requiring schema definition or ETL.

## Use cases
- run SQL queries on parquet files without loading them into a database
- query JSON and nested data in MongoDB or HDFS with SQL
- join data across multiple datastores like MongoDB and Hadoop in one query
- connect BI tools like Tableau or Excel to NoSQL data via JDBC/ODBC
- explore schema-free data in S3 or Azure Blob Storage with SQL
- avoid ETL overhead when analyzing multi-structured data

## When to choose
- you need SQL over schema-less or evolving data in NoSQL stores, Hadoop, or cloud object storage
- you want to connect existing BI tools to non-relational data via JDBC/ODBC
- you need distributed, federated queries joining multiple data sources
- you want to skip schema creation and data loading before analysis

## When to avoid
- your data lives in a traditional relational database with a fixed schema
- you need a lightweight embedded analytics engine for a single application
- you require a modern lakehouse stack with active ecosystem momentum (e.g., Trino, Presto, DuckDB)
- you need real-time streaming analytics rather than batch/interactive SQL

## Facets
- artifact type: application
- maturity: maintenance
- function: database, search-engine, etl, data-science
- domain: big-data, databases, analytics
- platform: jvm, windows, self-hosted, cloud
- tags: sql-query-engine, mpp, schema-free, hadoop, nosql, parquet, jdbc, odbc, distributed-query, apache-project, data-engineering, linux, macos, docker

## Member repositories
- apache/drill (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:06.411626+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 2026-08-30T03:00:05.405464+00:00, confidence not recorded.
  - readme: https://github.com/apache/drill (fetched 2026-08-28T04:06:06.411626+00:00, sha 4eca6cf30537)
  - homepage: https://drill.apache.org/ (fetched 2026-08-29T10:40:10.660162+00:00, sha 1cda9b46ce3f)
  - site_page: https://drill.apache.org/docs (fetched 2026-08-29T10:40:10.669862+00:00, sha e407ab03a282)
  - site_page: https://drill.apache.org/docs/getting-started (fetched 2026-08-29T10:40:10.672298+00:00, sha 4f49df30b6e1)
  - site_page: https://drill.apache.org/docs/architecture (fetched 2026-08-29T10:40:10.674843+00:00, sha 03e022f94715)
  - site_page: https://drill.apache.org/docs/tutorials (fetched 2026-08-29T10:40:10.677092+00:00, sha 7d771b435cc7)
  - site_page: https://drill.apache.org/docs/drill-on-yarn (fetched 2026-08-29T10:40:10.680732+00:00, sha 0ee4f927dade)
  - site_page: https://drill.apache.org/docs/install-drill (fetched 2026-08-29T10:40:10.684348+00:00, sha d0a4d8e814d6)
  - site_page: https://drill.apache.org/docs/configure-drill (fetched 2026-08-29T10:40:10.686655+00:00, sha 39c13f5732cd)
  - site_page: https://drill.apache.org/docs/connect-a-data-source (fetched 2026-08-29T10:40:10.688818+00:00, sha a7b2d963386a)
- Data as of 2026-08-30T08:39:29.467469+00:00.