Serverless Databases: DynamoDB vs. PlanetScale vs. Neon

Choosing a database is one of the most critical decisions when building a web application. When you're going serverless, the database choice becomes even more important. You want something that scales automatically, doesn't require much operational overhead, and ideally, plays well with your existing JavaScript/TypeScript stack. I've spent the last few years wrestling with this problem across different projects. Let's look at three popular options: DynamoDB, PlanetScale, and Neon.

Serverless Database Landscape

"Serverless" in the database world means different things to different vendors. Generally, you're looking for:

• Pay-as-you-go pricing: You only pay for what you use. No idle server costs.
• Automatic scaling: The database automatically scales up or down based on demand.
• Minimal operational overhead: You don't have to worry about patching, backups, or other database administration tasks.

Each of these databases takes a slightly different approach to delivering these benefits.

DynamoDB: The NoSQL Giant

DynamoDB is AWS's fully managed NoSQL database. It's a key-value and document database that's known for its extreme scalability and performance.

Pros and Cons

• Pros: Extremely scalable, fully managed, pay-per-request pricing, great integration with other AWS services.
• Cons: NoSQL data model can be limiting, complex to model relational data, can be expensive at high throughput, requires understanding of access patterns for optimal performance.

Code Example

Here's how you might interact with DynamoDB using the AWS SDK for JavaScript:

import { DynamoDBClient, GetItemCommand } from "@aws-sdk/client-dynamodb";
import { marshall, unmarshall } from "@aws-sdk/util-dynamodb";

const client = new DynamoDBClient({ region: "us-east-1" });

async function getItem(tableName: string, id: string) {
  const params = {
    TableName: tableName,
    Key: marshall({ id: id }),
  };

  const command = new GetItemCommand(params);

  try {
    const response = await client.send(command);
    if (response.Item) {
      return unmarshall(response.Item);
    } else {
      return null;
    }
  } catch (error) {
    console.error(error);
    return null;
  }
}

// Example usage
getItem("MyTable", "123")
  .then((item) => {
    console.log(item);
  })
  .catch((err) => {
    console.error(err);
  });

Gotcha: Notice the marshall and unmarshall functions. DynamoDB has its own data types, so you need to convert between JavaScript types and DynamoDB types. This can be a bit of a pain.

When to Use DynamoDB

DynamoDB is a great choice for:

• Applications with high read/write throughput.
• Use cases where you don't need complex relational queries.
• Workloads that are tightly integrated with the AWS ecosystem.

In a project last year, I used DynamoDB to store user session data for a high-traffic web application. The auto-scaling and pay-per-request pricing were a huge win.

PlanetScale: The Serverless MySQL

PlanetScale is a serverless MySQL database built on Vitess, a database clustering system originally developed at YouTube. It offers a familiar relational database experience with serverless benefits.

Pros and Cons

• Pros: Familiar SQL syntax, serverless scaling, non-blocking schema changes, branching for development, excellent developer experience.
• Cons: Limited MySQL feature set compared to traditional MySQL, can be more expensive than DynamoDB for simple key-value lookups, requires a Vercel or Netlify integration for the Hobby tier.

Code Example (with Drizzle ORM)

Here's how you might interact with PlanetScale using Drizzle ORM, a TypeScript ORM:

import { drizzle } from 'drizzle-orm/planetscale-serverless';
import { connect } from '@planetscale/database';
import { users } from './schema'; // Define your schema using Drizzle

const connection = connect({
  host: process.env.PLANETSCALE_HOST,
  username: process.env.PLANETSCALE_USERNAME,
  password: process.env.PLANETSCALE_PASSWORD,
});

const db = drizzle(connection);

async function getUserById(id: number) {
  const result = await db.select().from(users).where(eq(users.id, id));
  return result[0];
}

// Example usage
getUserById(1)
  .then((user) => {
    console.log(user);
  })
  .catch((err) => {
    console.error(err);
  });

Honestly, the developer experience with PlanetScale and Drizzle is fantastic. Defining your schema in TypeScript and having type-safe queries is a huge productivity boost.

When to Use PlanetScale

PlanetScale is a great choice for:

• Applications that need a relational database.
• Teams that are already familiar with MySQL.
• Projects where you want a smooth developer experience and advanced features like branching.

We deployed a Next.js application on Vercel using PlanetScale, and the integration was seamless. The non-blocking schema changes allowed us to iterate quickly without downtime.

Neon: Postgres Reimagined

Neon is a serverless Postgres database that separates storage and compute. This architecture allows for features like branching, bottomless storage, and instant scaling.

Pros and Cons

• Pros: Full Postgres compatibility, branching for development, serverless scaling, storage autoscaling, free tier available.
• Cons: Relatively new compared to DynamoDB and PlanetScale, potential vendor lock-in, performance characteristics might differ from traditional Postgres.

Code Example (with Prisma ORM)

Here's how you might interact with Neon using Prisma ORM, another popular TypeScript ORM:

import { PrismaClient } from '@prisma/client'

const prisma = new PrismaClient()

async function getUserById(id: number) {
  const user = await prisma.user.findUnique({
    where: { id: id },
  })
  return user
}

// Example usage
getUserById(1)
  .then((user) => {
    console.log(user);
  })
  .catch((err) => {
    console.error(err);
  });

The gotcha here is: Make sure your Prisma schema is correctly configured to connect to your Neon database. You'll need to provide the connection string in your .env file.

When to Use Neon

Neon is a great choice for:

• Applications that need full Postgres compatibility.
• Teams that are already familiar with Postgres.
• Projects where you want advanced features like branching and storage autoscaling.

I'm currently experimenting with Neon for a side project. The branching feature is incredibly useful for testing new features without affecting the production database.

Performance Considerations

Each of these databases has different performance characteristics. DynamoDB is generally the fastest for simple key-value lookups. PlanetScale and Neon are optimized for relational queries, but they might have higher latency for simple operations. It really depends on your use case. Benchmarking is key!

Pricing Comparison

Pricing can be complex, but here's a general overview:

Database	Pricing Model	Typical Use Cases
DynamoDB	Pay-per-request, storage costs	High-throughput applications, simple data models
PlanetScale	Based on reads, writes, and storage	Relational databases, moderate traffic
Neon	Based on compute, storage, and data transfer	Relational databases, complex queries

For small projects, the free tiers of PlanetScale and Neon might be sufficient. For larger projects, you'll need to carefully estimate your costs based on your expected usage.

Conclusion: Choosing the Right Database

There's no one-size-fits-all answer when it comes to serverless databases. DynamoDB is great for NoSQL workloads requiring extreme scale. PlanetScale offers a familiar MySQL experience with serverless benefits. Neon provides a fully-featured Postgres with innovative features like branching. Consider your data model, performance requirements, and team's expertise when making your decision. And always, always benchmark!