Serverless Databases and Storage
Traditional databases and serverless functions don't naturally fit together. Databases expect persistent connections from long-running applications. Serverless functions are ephemeral — they spin up, run briefly, and disappear. Understanding this mismatch helps you choose the right storage strategy.
The Connection Problem
A traditional database like PostgreSQL maintains a pool of connections. Each connection consumes memory on the database server. Limits are typically in the hundreds.
Serverless functions can scale to thousands of concurrent executions. If each opens a database connection, you quickly exhaust the limit. Even worse, functions might not cleanly close connections when they finish.
Serverless-Native Databases
Some databases are designed for serverless from the start:
DynamoDB (AWS) scales automatically with no connection limits. It's a NoSQL key-value store — different from relational databases but perfect for many serverless use cases.
FaunaDB provides a serverless-first relational database with a query language that works well with functions.
PlanetScale offers serverless MySQL with automatic scaling and branching for schema changes.
Neon provides serverless PostgreSQL that scales to zero and handles connection management automatically.
These databases handle the connection problem internally, making them natural fits for serverless architectures.
Connection Pooling for Traditional Databases
If you need a traditional database, use a connection pooler between your functions and the database:
Functions → Connection Pooler → Database
Many function connections → Few database connections
PgBouncer is a popular pooler for PostgreSQL. Prisma Data Proxy provides pooling as a service. Supabase includes built-in connection pooling.
The pooler maintains a small number of actual database connections and multiplexes function requests across them.
Choosing Your Storage Strategy
For simple key-value access, DynamoDB or similar NoSQL options work well and scale effortlessly.
For relational data with complex queries, use a serverless-native PostgreSQL like Neon, or traditional PostgreSQL with connection pooling.
For file storage, use object storage like S3 — it's inherently serverless and scales infinitely.
For caching, serverless Redis options like Upstash provide fast key-value access without connection management headaches.
The key is matching your storage choice to both your data needs and the serverless execution model.