Search Results for "high"

...It’s designed to make working with CSV files at scale easy and efficient, offering over 40 powerful subcommands for tasks like querying, sampling, splitting, deduplicating, and more. qsv is ideal for data engineers, analysts, and developers who need high-performance CSV manipulation on the command line.

High-performance xml pull reader/writer. The reader is almost zero-copy (use of Cow whenever possible) It is easy on memory allocation (the API provides a way to reuse buffers) It supports various encoding (with encoding feature), namespaces resolution, and special characters. Syntax is inspired by xml-rs. When using the serialize feature, quick-xml can be used with serde's Serialize/Deserialize traits.

...Cube was designed to work with all SQL-enabled data sources, including cloud data warehouses like Snowflake or Google BigQuery, query engines like Presto or Amazon Athena, and application databases like Postgres. Cube has a built-in relational caching engine to provide sub-second latency and high concurrency for API requests.

...Currently, the minimum supported Rust version is 1.36. Crossbeam welcomes contribution from everyone in the form of suggestions, bug reports, pull requests, and feedback. We also have the RFCs repository for more high-level discussion, which is the place where we brainstorm ideas and propose substantial changes to Crossbeam. If you'd like to learn more about concurrency and non-blocking data structures, there's a list of learning resources in our wiki, which includes relevant blog posts, papers, videos, and other similar projects. The Crossbeam project adheres to the Rust Code of Conduct. ...

Vortex is a high-performance toolkit designed for working with compressed Apache Arrow arrays, providing functionality for in-memory, on-disk, and over-the-wire data handling. It aims to be an advanced successor to Apache Parquet, offering dramatically faster random access reads and scans, while maintaining similar compression ratios. Vortex's modular design allows for extensibility, enabling developers to implement custom encodings for efficient data management, particularly for large-scale columnar datasets.

...Clean syntax highlighted display of JSON data, omitting quotes around object keys, closing object and array delimiters, and trailing commas. Expand and collapse objects and arrays so you can see both the high- and low-level structure of the data.