Data warehouses
Analytical databases such as BigQuery, Snowflake, Redshift or PostgreSQL-based warehouses.
Where we use it
- Business intelligence
- Cross-system reporting
Strengths
- Fast analytical queries
Considerations
Trade-offs worth knowing before you choose it.
- Query-based costs need governance
Data warehouses is a trademark of its owner. Listing it describes work we offer and does not imply a partnership or certification.
Services that use Data warehouses
Data engineering
Ingestion, transformation and orchestration pipelines, data warehouses and quality checks connecting operational systems to analytics.
Data analytics
Exploratory analysis, metrics definitions, cohort and funnel analysis, forecasting and statistical evaluation of business data.
Business intelligence
Self-service BI and operational dashboards with governed metrics, row-level access and scheduled reports.
More in databases and storage
- PG
PostgreSQL
A powerful open-source relational database with row-level security, JSONB and rich indexing.
- My
MySQL
The widely deployed open-source relational database.
- Ma
MariaDB
A community-developed MySQL-compatible database.
- MS
Microsoft SQL Server
Microsoft's enterprise relational database.
- Mo
MongoDB
A document database for flexible, evolving data structures.
- Rd
Redis
An in-memory data store for caching, rate limiting, queues and real-time data.
- SL
SQLite
An embedded SQL database in a single file.
- ES
Elasticsearch / OpenSearch
Full-text search and analytics engines.
Have a Data warehouses project in mind?
New build, rescue or modernisation — share what you have and where you want to get to.