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Querybook

querybook.org

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Spec score 7.1 #25 of 31 in SQL Query Tools

Spec sheet

Product
Querybook is an open-source big data IDE for discovering, creating, and sharing data analyses, queries, and tables.Read 3 Oct 2026 · querybook.org
Audience
The site describes Querybook as a tool for engineers and data scientists.Read 3 Oct 2026 · querybook.org
Deployment
Querybook runs in Docker; the site describes a Docker Compose demo and production deployment options including Kubernetes.Read 3 Oct 2026 · querybook.org
API
Users can create API access tokens and send them in the api-access-token request header for authentication.Read 2 Oct 2026 · querybook.org
Integrations
Documented query engines include Presto, Hive, Druid, Snowflake, BigQuery, MySQL, SQLite, PostgreSQL, SQL Server, and Oracle.Read 2 Oct 2026 · querybook.org
Support
The site provides a Slack community and lists [email protected] as a contact email.Read 3 Oct 2026 · querybook.org
Access controls
Environment access can be configured as public, hidden, or shareable, with private environments managed through user access controls.Read 3 Oct 2026 · querybook.org
AI features
The optional AI Assistant plugin can generate and edit SQL from text prompts, fix failed SQL, suggest SQL completions, and search tables and queries in natural language when its vector store is enabled.Read 2 Oct 2026 · querybook.org
Authentication
Documented authentication options include username and password, OAuth including Google Cloud OAuth, and LDAP.Read 3 Oct 2026 · querybook.org
Charts and scheduling
Users can create charts in DataDocs and schedule automatic DataDoc updates at set intervals.Read 3 Oct 2026 · querybook.org
Collaborative notebooks
DataDocs combine rich text, queries, and charts, and support real-time collaboration.Read 3 Oct 2026 · querybook.org
Exports and notifications
Documented options include Google Sheets and Python exports, plus email and Slack notifications.Read 2 Oct 2026 · querybook.org
Infrastructure requirements
The architecture documentation lists a database, Redis, Elasticsearch, and remote storage as infrastructure components, with MySQL recommended for the database.Read 3 Oct 2026 · querybook.org
Notifications
Query completion and DataDoc invitations can generate email or Slack notifications.Read 3 Oct 2026 · querybook.org
Query analytics
Querybook analyzes executed queries to provide lineage, example queries, frequent-user information, and search and autocomplete ranking.Read 3 Oct 2026 · querybook.org
Query editor
The query editor provides table-aware autocompletion, syntax highlighting, and table information on hover or click.Read 3 Oct 2026 · querybook.org
Query engines
Documented query engines include Presto, Hive, Druid, Snowflake, BigQuery, MySQL, SQLite, PostgreSQL, SQL Server, and Oracle.Read 3 Oct 2026 · querybook.org
Result storage and export
Query results can be stored in a database, S3, Google Cloud Storage, or local files, and exported to Google Sheets or Python.Read 3 Oct 2026 · querybook.org
Scale guidance
The setup guide describes single-machine setup for trying Querybook with fewer than five users and multi-machine setup for scaling to thousands.Read 2 Oct 2026 · querybook.org
Security advisory
The security advisories page reports a reflected XSS issue affecting versions before 3.14.2 when OAuth or Okta OAuth authentication was configured, with 3.14.2 listed as patched.Read 2 Oct 2026 · querybook.org

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