{"repo":"mag1cfrog/timeseries-table-format","free":true,"listed":false,"github":"https://github.com/mag1cfrog/timeseries-table-format","clone":"git clone https://github.com/mag1cfrog/timeseries-table-format.git","description":"Rust-native time-series table format with gap/overlap tracking and SQL queries","language":"Rust","stars":17,"topics":["analytics","arrow","data-engineering","data-lake","database","datafusion","lakehouse","parquet","roaring-bitmaps","rust"],"license":"MIT","category":"databases-storage","readme_excerpt":"timeseries-table-format Stop managing Parquet files. Start managing time-series tables. A Rust-native table format with coverage tracking, overlap-safe ingestion, and DataFusion SQL for local time-series data. Documentation Python Rust Early MVP: APIs and on-disk layouts may change before v1.0. Built for time-series data timeseries-table-format turns local Parquet segments into self-contained, append-only tables. It tracks which chronological windows exist for each entity, rejects overlapping appends, and exposes the result through DataFusion SQL. Use a Timestamp, Int64, or UInt64 column as the ordered index. The table format handles metadata, transactions, coverage, and segment discovery. Need Built-in support --- --- Know whether a time range is covered Coverage indexes and gap queries Prevent duplicate time windows Per-entity overlap detection Query many Parquet segments DataFusion SQL with segment pruning Run without Spark or a database server Rust core, Python package, and CLI It is a good fit for market data, sensor pipelines, backtesting systems, and other incremental time-series workloads that live on a local filesystem. A taste of the Python API The Python documentation walks through installation, ingestion, and queries. Performance In the repository's 73 million row NYC taxi benchmark, bulk ingestion was 7.7x faster than ClickHouse and 27x faster than PostgreSQL on the tested hardware and configuration. See the benchmark methodology and results for the workloads, en","default_branch":null,"files":null,"tree":[],"storefront":"/r/mag1cfrog","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/mag1cfrog/timeseries-table-format/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}