This guide shows best practices for connecting to relational databases with Serverless Functions.
Consider a traditional Node.js server connecting to a SQL database. When a request is made to your application, the server opens a connection to the database to execute a SQL query. After completion, the data is returned and the connection is closed.
At a large scale, creating a connection to your database on every request can exhaust server memory usage and hit the maximum number of connections allowed. One solution is to pay for more memory, and another is to use connection pooling.
Pooling is one solution to prevent your application from exhausting all available database connections. Rather than opening a connection with every request, connection pooling allows us to designate a single "pooler" that keeps an active connection to the database. When a request is made that would read from the database, the pooler finds an available connection rather than creating a new connection.
Traditional relational databases were built for long-running compute instances, not the ephemeral nature of serverless functions.
Serverless Functions are stateless and asynchronous. They are not designed for persistent connections to a database. It's easier to exhaust available database connections because functions scale immediately and infinitely when traffic spikes occur.
When a function is invoked, a connection to the database is opened. Upon completion, the connection is closed. Similar to a Node.js server, we want to maximize connection reuse. However, this requires different solutions in serverless environments than connection pooling.
Open source solutions like serverless-mysql and serverless-pg attempt to bring connection pooling to serverless environments. By storing variables outside the scope of the function, these solutions can create a connection pool in between invocations. However, there is no guarantee of connection reuse. Therefore, we recommend other solutions.
Services Vercel Postgres, Supabase (which uses PostgREST), Hasura, or AWS Aurora Data API expose a managed API layer on top of the underlying database. This allows you to execute SQL statements from any application over HTTP without using any drivers or plugins. Further, you don’t need to manage a connection pool or VPC.
These Data APIs don’t require a persistent connection to the database. Instead, they provide a secure HTTP endpoint where you can run your SQL statements without managing connections.
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Vercel has a suite of storage products, including:
- Vercel KV: Durable Redis servers
- Vercel Postgres: Serverless SQL servers
- Vercel Blob: Large file storage
- Vercel Edge Config: Global, low-latency data stores
See our docs to learn which product best suits your use-case.
Depending on your data workload, you might explore using other storage solutions that don’t require persistent connections. For example DynamoDB.
Vercel also offers Edge Functions, which use a slim runtime that doesn’t allow all Node.js APIs. Therefore, when using databases with Edge Functions, you are forced to use solutions that align with the best practices for connecting to databases (like using HTTP-based APIs or connectionless data providers).