pinterest / querybook

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

Querybook

Querybook is a Big Data IDE that allows you to discover, create, and share data analyses, queries, and tables. Check out the full documentation & feature highlights here.

Features

• 📚 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

Prerequisite

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

Configuration

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...

Authentication

• User/Password
• OAuth
  • Google Cloud OAuth
  • Okta OAuth
  • GitHub OAuth
  • Auth0 OAuth
• LDAP

Metastore

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

Notification

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

• Email
• Slack

User Interface

Query Editor

Charting

Scheduling

Lineage & Analytics

Contributing Back

See CONTRIBUTING.