Model your business. DataJoinery builds the data warehouse.
A collaborative, live data modelling platform. Design your model once, and DataJoinery generates the Snowflake data warehouse, the pipelines that load it from your Apache Iceberg data lake, and the tests, lineage and documentation that keep it trusted.
Apache Iceberg data lake
Snowflake data warehouse
MCP for AI agents
Built on open, cloud-native foundations
- Snowflake
- Apache Iceberg
- Google Cloud
- AWS
- Microsoft Azure
One platform, from raw data to trusted answers.
Land data in an open Apache Iceberg data lake, let DataJoinery pipelines build your Snowflake data warehouse, and serve the results to BI tools and AI agents.
Source systems
Operational systems, applications and files, connected from within DataJoinery.
Iceberg data lake
Raw data lands in open Apache Iceberg tables, kept in an open format you control.
DataJoinery pipelines
Generated SQL tasks load, historise and test every layer, pushed down to Snowflake.
Snowflake data warehouse
A Data Vault core of hubs, links and satellites, generated from your model.
Answers
Facts, dimensions and bridges for BI tools, and for AI agents through MCP.
Insert-only SQL tasks, run where your data lives
Automated unit tests after every pipeline run
Role-based and row-level security with secure views
Design the model. DataJoinery does the rest.
Cloud-based with no setup required, so it’s quick and easy to get started.
Design the model and define the metrics that matter
The enterprise data warehouse core entities are generated, along with the data mart definitions.
Map the source data and apply business rules
The SQL tasks and data pipelines are generated automatically.
Run the pipeline, load the data, share with the right audience
Role-based and row-level security is applied, and data reaches stakeholders through secure views.
Pipeline run
Data warehouse load
- customer_hLoaded
- order_hLoaded
- order_lLoaded
- order_item_dclLoaded
- Status tracking satellitesLoaded
- Point-in-time and bridge tablesLoaded
- Unit testsPassed
Your data model, ready for AI agents.
Each DataJoinery environment runs its own MCP server. Connect Claude or any MCP client, sign in with OAuth 2.1, and let agents explore your model, trace lineage and check pipeline health in plain language.
- Search conceptual entities, facts and dimensions
- Trace field-level lineage for any logical entity
- Read the SQL generated for each physical entity
- Check pipeline runs and drill into failed tasks
DataJoinery MCP
Did any production pipelines fail today?
get_pipeline_runsstatus Failed, today
No failed runs in production today. Every pipeline completed and its unit tests passed.
What feeds the order_l link?
get_lineage_summary_for_logical_entity
order_l is loaded from the orders feed and links each order to customer_h and order_h. Its effectivity satellite tracks which relationships are active.
Built to free your team from data drudgery.
Bridge the divide between your data requirements and your current data complexities, with a business and data-driven approach that fits your needs.
Modernise
Replace outdated data architecture with a cloud data platform that scales as your business grows.
Free up skills
Automate data drudgery so your technical team can make better use of their skills and raise performance.
Fast
Develop rapidly with best practice built in, and keep the flexibility and control to adapt the architecture as you plan.
Integrate
Easily integrate and augment new and existing technology and data sources.
Lower cost
Cloud-based, so there are no servers to run and less admin, with easy access to support and training.
Trusted data
Automated unit tests run after every pipeline load, so issues surface before they reach your reports.
For data and software engineers
A toolset that fits your existing skills, is easy to maintain and works with open technology, so analysts and engineers are freed up for what they do best.
How DataJoinery helps engineers
Start with a small use case.
Speak to a DataJoinery data specialist today.