Querybook is a Big Data Querying UI, combining collocated table metadata and a simple notebook interface.


  • ? Organize analyses with rich text, queries, and charts
  • ✏️ Compose queries with autocompletion and hovering tooltip
  • ? Use scheduling + charting in DataDocs to build dashboards
  • ? Live query collaborations with others
  • ? Add additional documentation to your tables
  • ? Get lineage, sample queries, frequent user, search ranking based on past query runs

Getting started


Please install Docker before trying out Querybook.

Quick setup

Pull this repo and run make. Visit https://localhost:10001 when the build completes.

For more details on installation, click here


For infrastructure configuration, click here
For general configuration, click here

Supported Integrations

Query Engines

  • Presto
  • Hive
  • Druid
  • Snowflake
  • Big Query
  • MySQL
  • Sqlite
  • PostgreSQL
  • and many more...


  • User/Password
  • OAuth
    • Google Cloud OAuth
    • Okta OAuth
    • GitHub OAuth
  • LDAP


Can be used to fetch schema and table information for metadata enrichment.

  • Hive Metastore
  • Sqlalchemy Inspect
  • AWS Glue Data Catalog

Result Storage

Use one of the following to store query results.

  • Database (MySQL, Postgres, etc)
  • S3
  • Google Cloud Storage
  • Local file

Result Export

Upload query results from Querybook to other tools for further analyses.

  • Google Sheets Export
  • Python export


Get notified upon completion of queries and DataDoc invitations via IM or email.

  • Email
  • Slack

User Interface

Query Editor



Lineage & Analytics