pinterest/querybook
Querybook is a Big Data Querying UI, combining collocated table metadata and a simple notebook interface.
repo name | pinterest/querybook |
repo link | https://github.com/pinterest/querybook |
homepage | https://www.querybook.org |
language | TypeScript |
size (curr.) | 37339 kB |
stars (curr.) | 341 |
created | 2020-03-05 |
license | Apache License 2.0 |
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
- SQL Server
- Oracle
Authentication
- User/Password
- OAuth
- Google Cloud OAuth
- LDAP
Metastore
Can be used to fetch schema and table information for metadata enrichment.
- Hive Metastore
- Sqlalchemy
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.
- Slack
User Interface
Query Editor
Charting
Scheduling
Lineage & Analytics
Contributing Back
See CONTRIBUTING.