typedorm VS dynamodb-toolbox

To that end, you'll say. "Well what do you do then?" And from my reading, it appears we end up back at Object Oriented Programming 🎉. [DynamoDb Toolbox] seems like a moderately popular library for accomplishing this in node. I've also talked with a friend who makes heavy use of it and he had no complaints. A newer player in the space is TypeDORM taking heavy inspiration from TypeORM and using DynamoDb Toolbox under the hood. Personally I've yet to use this tool but it's for sure on my short list to try out.

As a result, I developed dynaglue for this purpose, and highly recommend the use of something like it when developing with DynamoDB (alternatives I've seen include DynamoDB Toolbox, TypeORM and DynamoDB OneTable).

Enter DynamoDB-Toolbox — a lightweight and type-safe query builder for DynamoDB. It already knows everything about your table schemas and access patterns, so why not use that to supercharge your MCP Server?

And this is just a simple query - imagine dealing with more complex needs. Sure, there are tools trying to make this better like dynamodb-toolbox by providing a more friendly API. While they are great at what they do - they make code look better and easier to work with - but at the same time they can't change DynamoDB fundamental capabilities. They're band-aids that make development less painful, but don't address the fundamental limitations.

One of them was that it had originally been coded in JavaScript. Although Jeremy rewrote the source code in TypeScript in 2020, it didn't handle type inference, a feature that I eventually came to implement myself in the v0.4.

If you have in mind features that I missed, or would like to see some of the ones I mentioned prioritised, please comment this article and/or create an issue or open a discussion on the official repo with the v1 label 👍

For instance, here is an example of the same UpdateCommand with one of those wrappers, DynamoDB-Toolbox:

It's been mature enough for at least four years.

1. Not an issue for me. Connection reuse support in Lambda is quite good

2. NoSQL is a good skill to keep your in bucket anyhow. DynamoDB is a different approach, but much of the same tenets you'll find in other NoSQL databases still apply. Using tools like dynamodb-toolbox [1] help greatly with paradigm shifts into Dynamo.

3. True. Ask yourself how much this matters. How likely is it that you'll need to support another cloud provider for a single product? In 20 years I've seen a platform provider switch exactly once. And DynamoDB can be exported easily.

4. Nope. But there are things to learn about cold starts; how to structure code, where to initialize things, which things should be singletons, etc.

5. Depends on the situations and needs. The right tool for the right job, if you will. I've written GraphQL servers that run on lambda which serve 300k users daily. I've also done the same using Fargate/ECS et al. Much of the decisions revolve around complexity of execution and cost factors (e.g. the cost and complexity of running lambda's to process data often versus a Fargate service). You're getting into Software Architecture now.

6. Again, depends on the situation. You'll need to start thinking about what individual services/components/things are doing, what they need, and how they need to run. Gather that information, and then start cost comparisons using the pricing tools the provider has.

[1] https://github.com/jeremydaly/dynamodb-toolbox

Note that all these entities will belong to the same DynamoDB table. We define only one partition key and one sort key for this table: both of type string. Key is the values we provide for these keys. As you can imagine, this quickly can become a bit tangled mess. Therefore I recommend to express this 'schema' (e.g. of what types of keys we lay over our base table) in code. Later in this article I will show how this can be accomplished using the DynamoDB Toolbox framework.