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Querybook is a big data IDE that combines a notebook-style query editor with table metadata for discovering and sharing analyses.

Open-source alternative to:HexMode Analytics

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What is it?

Querybook is a web-based Big Data IDE for writing, organizing, and sharing SQL queries, analyses, and tables. Analyses are built as DataDocs, which mix rich text, queries, and charts in a notebook-like layout.

The query editor offers autocompletion and hover tooltips against table metadata. Table documentation, lineage, sample queries, and search ranking are drawn from past query runs, so users can see how data is actually used. DataDocs can also be scheduled and charted to serve as simple dashboards, and multiple people can collaborate on a query live.

Querybook connects to engines such as Presto, Hive, Snowflake, BigQuery, MySQL, and PostgreSQL, and reads metadata from Hive Metastore, SQLAlchemy inspection, or AWS Glue. It supports user/password, OAuth, and LDAP login, and sends notifications by email or Slack.

Key features

  • 01Write analyses as DataDocs combining rich text, queries, and charts.
  • 02Autocompletion and hover tooltips in the query editor based on table metadata.
  • 03Table documentation, lineage, and sample queries derived from past query runs.
  • 04Scheduling and charting to build dashboards from DataDocs.
  • 05Live collaborative query editing.
  • 06Result export to Google Sheets or Python.

Use cases

  • Data teams sharing analyses and recurring reports across an organization.
  • Exploring large warehouse tables with metadata, lineage, and past query usage.
  • Building lightweight scheduled dashboards on top of SQL queries.
  • Running queries against Presto, Hive, Snowflake, or BigQuery from one interface.

Quick start

  1. 1

    Install Docker, which is required before trying Querybook

  2. 2

    Pull the repo and run make from its directory

    make
  3. 3

    Visit http://localhost:10001 once the build completes

Things to know

  • Requires Docker and a multi-step build to run locally.
  • Needs a configured query engine and metastore to be useful with your own data.

Topics

#sql#big-data#notebook#data-analysis#data-catalog#presto#hive#typescript#analyses#celery

FAQ

What is querybook?
Querybook is a big data IDE that combines a notebook-style query editor with table metadata for discovering and sharing analyses. Querybook is a web-based Big Data IDE for writing, organizing, and sharing SQL queries, analyses, and tables. Analyses are built as DataDocs, which mix rich text, queries, and charts in a notebook-like layout.
Is querybook free to use? What license does it have?
querybook is open source under the Apache-2.0 license. Check the license terms before using it in commercial products.
Is querybook still maintained?
Updated within 6 months. The last commit to querybook was on Sep 16, 2026.
What can I use querybook for?
Data teams sharing analyses and recurring reports across an organization. Exploring large warehouse tables with metadata, lineage, and past query usage. Building lightweight scheduled dashboards on top of SQL queries. Running queries against Presto, Hive, Snowflake, or BigQuery from one interface.
How do I install querybook?
Install Docker, which is required before trying Querybook Pull the repo and run make from its directory: make Visit http://localhost:10001 once the build completes
Where can I get querybook?
The source code and installation instructions are on GitHub: https://github.com/pinterest/querybook

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