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PostgreSQL Development

PostgreSQL is an open-source relational database known for reliability, strong data integrity guarantees and extensibility, including vector search for AI workloads.

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Why We Use It

PostgreSQL handles complex relational data reliably at scale, and its vector extension support makes it a practical single database for both application data and AI retrieval use cases.

Our Expertise

We use PostgreSQL as the default relational database for custom software, SaaS platforms and RAG systems, applying careful indexing and query design as data volume grows.

Use Cases

Typical Use Cases

Application Data Storage Core relational data for SaaS platforms and custom software.
Vector Search for RAG Storing and querying embeddings for retrieval-augmented generation.
Reporting & Analytics Complex queries and aggregations supporting dashboards and reporting.

How It Fits Our Architecture

PostgreSQL typically sits behind an application layer (PHP, Python or Node.js), accessed through prepared statements, with Redis layered in front for caching where needed.

Related

Related Services

Related Technologies

Django Redis AWS

FAQ

Frequently Asked Questions

Both are strong relational databases — we choose based on the specific project's requirements, including whether native vector search support is needed for AI features.

Yes — with vector extension support, PostgreSQL can store and query embeddings, allowing application data and retrieval data to live in one system.

Well, with the right indexing, query optimization and read-replica strategy applied as data volume and query load grow.

Building With PostgreSQL?

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