DynamoDB cannot run JOINs and aggregations natievly, usually it is solved by exporting to Athena (for big datasets) or writing a one-off script.
We took a different approach and built a local SQL engine on top of SQLite that can run JOINs, SUM, AVG, MIN, MAX and automatically selects best GSI for efficient queries.
It is still Scans and Queries under the hood and is limitet to joins over hash and range keys, but it efficiently replaces one off scripts and simplifies life of people (and AI agents) who are used to SQL and it gives familiar abstraction where you need to think less about how it works and focus on the result.
DynamoDB cannot run JOINs and aggregations natievly, usually it is solved by exporting to Athena (for big datasets) or writing a one-off script.
We took a different approach and built a local SQL engine on top of SQLite that can run JOINs, SUM, AVG, MIN, MAX and automatically selects best GSI for efficient queries.
It is still Scans and Queries under the hood and is limitet to joins over hash and range keys, but it efficiently replaces one off scripts and simplifies life of people (and AI agents) who are used to SQL and it gives familiar abstraction where you need to think less about how it works and focus on the result.