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A time series database optimized for managing high-cardinality data

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TRustDB

Build & Tests

Welcome to TRustDB (Time series Rust DataBase), a database optimized for handling high-cardinality time series data. The technical report can be found here.

By Desmond Cheong & Nick Young

Getting Started

  • Populate a .env file with the path of the data folder. We've suggested a default in the sample.env file.

Key Design Choices

  • To support efficient queries, an inverted index is constructed that maps from label key-value pairs and metric names to series.
  • To reduce the storage footprint of this metadata, the inverted index is compressed into a Finite State Transducer (FST).
  • To speed up query evaluation, queries are rewritten and evaluated in Disjunctive Normal Form (DNF).

More details can be found in the technical report.

Roadmap & Contributing

This database is far from complete and we have a lot more ideas to experiment with. Some of the things on our mind can be found on the issues page.

Contributions are welcome!

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A time series database optimized for managing high-cardinality data

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  • Rust 84.2%
  • Python 15.3%
  • Shell 0.5%