Building a Full-Stack App with Just PostgreSQL: 11 Unorthodox Use Cases

Modern web development is filled with countless specialized tools, leading to complex stacks and mounting costs. But what if you could achieve most of your application's needs using a single, powerful tool? This article explores how PostgreSQL, the extensible relational database, can replace a significant portion of your tech stack.

1. Storing and Querying Unstructured Data (JSONB)

Contrary to the SQL vs. NoSQL debate, PostgreSQL natively supports unstructured data via the JSONB data type. This allows you to store dynamic JSON objects and perform efficient queries on them, eliminating the need for a separate document database in many cases.

2. Cron Jobs (pg_cron)

The pg_cron extension enables you to schedule recurring SQL commands directly within the database. This can handle tasks like data aggregation, cleanup, or reporting, removing the dependency on external cron services or scheduler SaaS products.

3. In-Memory Caching (Unlogged Tables)

By creating UNLOGGED tables and configuring them to use shared buffers, you can create a high-performance, RAM-based cache. This serves as a practical alternative to dedicated in-memory databases like Redis for many caching scenarios, especially when combined with automation for clearing expired data.

4. Vector Database for AI (pgvector/pgai)

For AI applications using RAG (Retrieval-Augmented Generation), the pgvector extension adds a vector data type and enables similarity searches (e.g., nearest neighbor). Extensions like pgai can further handle vectorization of your dataset entirely within SQL, challenging the need for a separate vector database.

5. Full-Text Search (TSVECTOR)

PostgreSQL has robust, built-in full-text search capabilities. Using the TSVECTOR data type and generalized inverted indexes (GIN), you can implement a powerful search engine that handles ranking and typo-tolerant queries, reducing reliance on external services like Elasticsearch or Algolia.

6. GraphQL API (pg_graphql)

The pg_graphql extension can automatically generate a GraphQL API from your database schema. This allows frontend clients to query the database directly using GraphQL, often eliminating the need to build and maintain a custom backend API layer.

7. Real-Time Synchronization (ElectricSQL)

While not a pure extension, libraries like ElectricSQL provide a sync layer between PostgreSQL and frontend applications. This enables real-time data updates for users without the complexity of manually managing WebSockets or polling, offering an alternative to platforms like Firebase or Supabase for real-time features.

8. Authentication & Security (pgcrypto/pgjwt)

By combining extensions like pgcrypto for password hashing and pgjwt for generating JSON Web Tokens, you can implement a secure authentication system directly within the database. Furthermore, PostgreSQL's Row Level Security (RLS) policies can enforce data access rules based on the authenticated user, ensuring users only access their own data.

9. Analytics & Time-Series Data (pg_mooncake)

Extensions such as pg_mooncake optimize PostgreSQL for time-series data analytics by introducing column-store tables and efficient execution. This can transform your database into a powerful analytics engine, capable of handling large volumes of time-stamped data which can then be visualized with tools like Grafana.

10. RESTful API (PostREST)

Tools like PostREST can automatically generate a RESTful API endpoint from your PostgreSQL database schema. This provides immediate CRUD (Create, Read, Update, Delete) operations, filtering, and pagination over HTTP/JSON, significantly accelerating backend development.

11. Server-Side HTML & UI (Theoretical)

Pushing the concept to its limit, it's theoretically possible to store and serve UI components (HTML, CSS, JS) directly from the database. Some experimental approaches even attempt to run React Server Components within PostgreSQL, aiming to colocate data and UI logic intimately.