- Q1: Preliminary DuckDB extension (with limited subset of planned features)
- Q2: PuffinDB 0.1 with basic distributed query planner (filter pushdown)
- Q4: PuffinDB 1.0 with advanced distributed query planner (including support for full TPC-H benchmark)
- 2024: PuffinDB 2.0 (including support for full TPC-DS benchmark)
Features will be implemented in the following order. Please start an Idea
discussion to discuss any element of this proposed roadmap.
- Domain name
- Logo design
- Core architecture design
- Temporary GitHub repository
- Permanent GitHub organization
- DuckDB extension repository (private for now)
- PuffinDB engine repository (private for now)
- Continuous integration framework
- Unit testing framework
- Integration testing framework
- Project website
- DuckDB extension (with minimal set of features)
- Airbyte connector framework
- Support for
SELECT THROUGH
syntax - Authentication
- Authorization
- Catalog serverless function
- Lakehouse template
- Lakehouse catalog integration (AWS Glue Data Catalog, Amazon DynamoDB, and Amazon RDS)
- Read queries against Lakehouse tables executed by DuckDB
- Write queries against Lakehouse tables executed by Amazon Athena
- Engine serverless function
- Engine template
- Remote query engine running on AWS Lambda functions
- Query logs recorded as JSON values in Redis cluster (using Amazon ElastiCache for Redis)
- Query proxy
- PRQL to SQL translator
- Malloy to SQL translator
- SQL dialect converter
- Remote query engine running on Monostore
- Basic distributed query planner
- Partition caching on AWS Lambda function
- Query result caching on Object Store
- Query result caching on CDN (Amazon CloudFront)
- AWS Marketplace provisioning
- Microsoft Azure support
- Joins across tables managed by different Lakehouse instances
- Asynchronous invocations over Apache Arrow
- Arrow Database Connectivity support
- Concurrent suport for multiple Lakehouse instances
- Advanced distributed query planner
- Delta Lake support
- Apache Hudi support
- Joins across heterogenous tables using different table formats
- AWS Fargate support
- Google Cloud support