Drizzle vs DynamoDB for Solo Developers

Quick Comparison

Drizzle Overview

Drizzle ORM lets you write SQL queries in TypeScript with full type safety. The API follows SQL patterns directly, so joins, subqueries, and aggregations all work the way you expect them to. The package is small, fast, and works with Postgres, MySQL, and SQLite.

For solo developers, Drizzle is practical. You get the safety of typed queries without the learning curve of a new paradigm. If you know SQL, you know Drizzle. Schema changes go through drizzle-kit migrations, and you can pair it with any database provider you want.

The simplicity is the point. Drizzle does queries. It does them well. It does nothing else.

DynamoDB Overview

DynamoDB is Amazon's fully managed NoSQL database. It uses a key-value and document data model where you access items by partition key and optional sort key. Designed for massive scale, DynamoDB can handle millions of requests per second with single-digit millisecond latency.

The learning curve is the catch. DynamoDB requires you to think about your data access patterns upfront. You design your table structure around your queries, not your entities. This means single-table design, Global Secondary Indexes (GSIs), composite keys, and a lot of planning before you write your first line of application code.

For solo developers, DynamoDB's pay-per-request pricing can be attractive for low-traffic applications. You pay nothing when nobody is using your app. But the development overhead of designing and maintaining DynamoDB tables is significant compared to using SQL.

Head-to-Head Comparison

When to Pick Drizzle

Pick Drizzle when your data is relational and you want to query it flexibly. If you need to join users with orders, filter by date range, aggregate revenue by month, or run any ad-hoc query, SQL is the right tool and Drizzle makes SQL type-safe.

It is the right choice when you do not want to design your data model around specific access patterns. With SQL, you normalize your data and query it however you need. If a new feature requires a new query pattern, you write the query. With DynamoDB, a new access pattern might require a new GSI or a table redesign.

Choose Drizzle for any project where developer velocity matters more than theoretical infinite scale. You will build features faster with SQL than with DynamoDB's access-pattern-first approach.

When to Pick DynamoDB

Pick DynamoDB when you are building on AWS and your data access patterns are simple and well-defined. Key-value lookups, time-series data, session storage, and high-throughput write workloads are where DynamoDB excels.

It also makes sense when you genuinely need to scale to millions of requests per second with consistent latency. DynamoDB's architecture guarantees single-digit millisecond response times regardless of table size. No Postgres instance can match that at extreme scale.

Choose DynamoDB if you are already deep in the AWS ecosystem, you are building with Lambda and API Gateway, and your data model naturally fits key-value access patterns. The tight integration with other AWS services is a real advantage in that context.

The Verdict

For most solo developers, Drizzle with a managed Postgres database is the better choice. SQL is more flexible, easier to learn, and faster to develop with. You can build virtually any application with a relational database, and the tooling ecosystem around SQL is mature and well-supported.

DynamoDB is a specialized tool for specialized problems. Unless your application has very simple access patterns with extremely high throughput requirements, the development overhead of DynamoDB design is not worth it for a solo developer.

The steep learning curve is the real issue. Single-table design, GSI projections, capacity planning, and the constraints of key-value access are all things that slow you down when you are trying to ship. A solo developer's most scarce resource is time, and DynamoDB demands a lot of it upfront.

Use Drizzle with Postgres. If you ever genuinely outgrow SQL (and most applications never do), you can introduce DynamoDB for specific high-throughput use cases while keeping your primary database relational.