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MongoDBAnnouncement
How We Used AI to Bring MongoDB to DynamoDB
Summary
AWS released ExtendDB, an open source adapter that lets DynamoDB workloads use pluggable storage backends, enabling them to run outside AWS. MongoDB built a storage backend for ExtendDB, allowing DynamoDB workloads to run on MongoDB anywhere, including on-premises and air-gapped environments, without changing application code. The backend maps DynamoDB concepts like partition keys, secondary indexes, transactions, and streams to MongoDB primitives, with tradeoffs such as handling numeric precision differences in the Rust layer. The project began as a hackathon experiment where an engineer used Claude Code to prototype the backend, which quickly produced a working component, then required several weeks of partnering with AWS to merge. The post emphasizes that AI changed the economics of such experiments, enabling the idea to move from thought to implementation quickly, and the backend is now available as open source.
Context
ExtendDB is an open source adapter that enables DynamoDB workloads to use different storage backends, allowing them to run on any infrastructure. MongoDB implemented a backend for ExtendDB, leveraging its flexible document model to map DynamoDB concepts.
Approach / What changed
Implemented a pluggable MongoDB backend for AWS’s ExtendDB adapter, mapping DynamoDB partition keys, secondary indexes, conditional writes, transactions, and streams to MongoDB primitives. Numeric precision differences are handled by performing comparisons in the Rust layer. The project started as a hackathon prototype using Claude Code, then went through AWS’s RFC process to merge.
Takeaways
ExtendDB allows DynamoDB workloads to run on any infrastructure by using pluggable storage backends, and MongoDB’s backend enables running DynamoDB workloads on MongoDB anywhere.
The MongoDB backend maps DynamoDB concepts like partition keys, secondary indexes, transactions, and streams to MongoDB primitives, with tradeoffs such as handling numeric precision differences in the Rust layer.
The project was prototyped using Claude Code during a hackathon, demonstrating how AI can reduce the cost of experimentation and enable quick validation of ideas.
FAQ
How does the MongoDB backend handle DynamoDB's numeric precision?
DynamoDB supports up to 38 digits of precision, while MongoDB's Decimal128 supports 34. The backend performs numeric comparisons in the Rust layer instead of pushing them to MongoDB to avoid breaking comparisons.
What DynamoDB features does the MongoDB backend support?
It supports item keys and queries, secondary indexes, conditional writes, transactions, and streams. It maps these to MongoDB primitives like document fields, separate collections, session transactions, and stream-record documents.
How was the MongoDB backend for ExtendDB developed?
It started as a hackathon experiment where an engineer used Claude Code to prototype the backend. The initial prompt produced a working component by lunchtime, then required several weeks of partnering with AWS through their RFC process to merge.
Source and freshness
- Source
- mongodb.com
- Published
- Added to Yomu
Summaries are generated from the original by a language model. Check the original before relying on it.
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