Orbit
Xstreami
- About
- Services
- Blogs
- Careers
- Products
- Contact Schedule a Call
PostgreSQL for Analytics & Data Warehousing
Modern businesses need more than just transactional databases—they need fast, scalable analytics platforms to process massive datasets in real-time. PostgreSQL, with its advanced SQL features, parallel query execution, and extensibility, has become a top choice for building analytics and data warehousing solutions.
At Mafiree, we help organizations transform PostgreSQL into a powerful analytics engine. From real-time reporting with TimescaleDB, distributed queries with Citus, to seamless integration with BI tools like Tableau, Power BI, and Looker, we design solutions that deliver actionable insights without expensive proprietary data warehouses.
Why Choose PostgreSQL for Analytics & Warehousing?
- Native support for complex queries, JSON, and time-series data
- Scales horizontally with Citus for distributed PostgreSQL
- Integrates with ETL pipelines and BI tools for smooth reporting
- Extensions like TimescaleDB, PostGIS, FDWs for specialized workloads
- Cost-effective alternative to Oracle, Redshift, or Snowflake
Our PostgreSQL Analytics & Warehousing Services
Data Warehouse Design & Implementation
- Build PostgreSQL-powered data warehouses tailored to your business
- Schema design, indexing, and partitioning for high-performance analytics
- Optimize workloads with materialized views and query parallelization
Real-Time Analytics with PostgreSQL
- Enable time-series analytics with TimescaleDB
- Implement event-driven pipelines with Kafka + PostgreSQL
- Real-time dashboards powered by PostgreSQL + BI integrations
Distributed & Scalable Analytics
- Deploy Citus for distributed PostgreSQL clusters
- Handle billions of rows with sharding and parallel execution
- Multi-node architectures for high throughput workloads
BI & Reporting Integrations
- Connect PostgreSQL to Tableau, Power BI, Looker, Metabase
- Design custom ETL pipelines for smooth data ingestion
- Optimize query performance for reporting at scale
Advanced Analytics & Extensions
- Geospatial analytics with PostGIS
- Machine learning pipelines using PostgreSQL + Python/R integrations
- Foreign Data Wrappers (FDWs) to query external data sources
Common PostgreSQL Analytics Challenges We Solve
- Slow reporting queries on large datasets
- Inefficient schema design for analytics workloads
- Difficulty scaling PostgreSQL for warehousing needs
- Gaps in BI integrations or ETL performance
- Rising costs of proprietary data warehouses
FAQs – PostgreSQL for Analytics & Data Warehousing
Get in
touch with us
More than 6000 Servers Monitored
Happy Clients
Certified Database Administrators
24 x 7 x 365 Support
