Datascale — Next-gen Data Lineage & Discovery with LLMs
Datascale is a data lineage and discovery platform powered by AI/LLMs. It converts SQL transformations into a visual lineage graph, makes data assets searchable with AI, and provides a range of collaborative and governance-focused features to help data teams understand and navigate complex data ecosystems.
Overview
- Automatically map data lineage from SQL-based transformations and expose assets in a searchable, AI-assisted interface.
- Turn SQL models, DDL, DML, views, and pipelines into a navigable lineage graph.
- AI-powered search and knowledge exploration to quickly locate assets and contexts.
- Real-time synchronization via API with user-controlled data you send; no mandatory DB access required.
- Designed for large-scale lineage exploration with intuitive navigation, diagrams, and code visibility.
How It Works
- Simple setup and import: Bulk import your documents and data assets to begin building lineage within minutes.
- Automated lineage mapping: Datascale reverse-engineers SQL-based transformations (DDL, DML, views) to construct a comprehensive lineage graph.
- AI-powered discovery: Use natural language search and AI-assisted insights to find assets, dependencies, and context fast.
- Sync and control: Changes in your schema can be synced via API; you retain full control over what metadata is sent.
- Explore with AI: Leverage LLMs to answer questions, suggest follow-ups, and explore relationships across upstream and downstream assets.
Features
- From SQL to data lineage in minutes: auto-generate lineage graphs from SQL-based transformations and assets.
- AI-powered search: quickly locate assets and context with natural-language queries.
- Always synced: API-driven synchronization to reflect schema changes without direct DB access.
- Full lifecycle visibility: navigate upstream and downstream assets with ease; auto-zoom helps keep the focused asset in view.
- Diagrams and code in one view: connect lineage visuals with asset code and details side-by-side.
- Multi-model, multi-asset support: explore lineage across multiple models with working sets and VSCode-like navigation.
- Knowledge exploration with LLMs: interactive questions, context retrieval, and helpful follow-up suggestions.
- Shared AI workspace: real-time, multi-user team chat for collaborative analysis.
- Integrations: connect with popular third-party apps to extend workflows and data tooling.
- No database credentials required (secure data handling): import what you need and control data you send.
What You Can Do
- Visualize complex data dependencies and understand the big picture of data flows.
- Quickly retrieve relevant context and asset details for impact analysis, audits, or debugging.
- Collaborate with team members in a shared AI-enabled workspace for faster decisions.
- Trial the platform with a 14-day free trial to evaluate lineage accuracy and AI capabilities.
Integrations & API
- Seamless integration with your existing stack via API; ingest metadata by sending it to Datascale endpoints.
- No need for exposing database credentials; data sent to Datascale is under your control.
- Connects with thousands of platforms to sync images, emails, and other assets as part of your data workflow.
FAQ (Concise)
- Can Datascale work with existing SQL models and queries? Yes. It reverse-engineers SQL models from DDL (CREATE TABLE / CTAS), DML (INSERT INTO), views, etc.
- How do I try Datascale? It offers a 14-day free trial with full access; book a demo to set up a pilot.
- Can it infer the order of execution for lineage? Yes, by analyzing dependencies between data transformations.
- How do I API-integrate? Ingest metadata via the provided API endpoints; support is available for setup and troubleshooting.
Target Users
- Data engineers, data architects, analytics teams, and data leaders who need clear, scalable data lineage and rapid asset discovery.
Note
Datascale emphasizes privacy and control over data sent to the platform, enabling safe collaboration while mapping and exploring data lineage at scale.