Querybook is a web-based big data IDE for exploring datasets, composing queries and sharing analytical work.
Originally developed at Pinterest, it combines an SQL editor with documentation, visualization and collaboration facilities. Rather than treating queries as isolated snippets, Querybook lets teams organise them into richer analytical documents containing text, queries and charts. It is particularly suited to organisations where many people query shared data infrastructure and need an easier way to discover existing tables and previous work.
This is free and open source software.
Key Features
- Organises analytical work into DataDocs containing rich text, executable queries and visualizations.
- Provides an SQL editor with autocompletion and contextual information when hovering over database objects.
- Supports live collaboration so multiple users can work with queries together.
- Allows additional documentation to be attached to tables, improving the usefulness of a shared data catalogue.
- Records query history and uses previous executions to expose sample queries, frequent users and other discovery information.
- Provides table lineage information to help users understand relationships between datasets.
- Can schedule queries and combine their results with charts to create dashboards.
- Supports query engines including Presto, Hive, Druid, Snowflake, BigQuery, MySQL, SQLite and PostgreSQL.
- Can obtain schema and table metadata from Hive Metastore, AWS Glue Data Catalog and SQLAlchemy inspection.
- Stores query results in relational databases, object storage or local files.
- Can export query results to Google Sheets or Python for further analysis.
- Supports password authentication, LDAP and several OAuth identity providers.
Website: github.com/pinterest/querybook
Support:
Developer: Pinterest
License: Apache License 2.0
Querybook is written in TypeScript and Python. Learn TypeScript with our recommended free books and free tutorials. Learn Python with our recommended free books and free tutorials.
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