From 829ba7d840b3718267a7192d7fbe1959cfd85002 Mon Sep 17 00:00:00 2001 From: Eddie A Tejeda Date: Thu, 11 Dec 2025 17:15:09 -0800 Subject: [PATCH] Improve clarity of RivetDB description in README Rephrase description of RivetDB's architecture for clarity and conciseness. --- README.md | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 6f44f81..296f248 100644 --- a/README.md +++ b/README.md @@ -16,7 +16,7 @@ It provides a Trino-style SQL interface for querying remote data sources without RivetDB takes inspiration from [DuckDB](https://duckdb.org/) and the Small Data community, which has shown how much you can get out of a single machine when you pair simplicity, vectorized execution, and efficient columnar formats. RivetDB applies that same thinking to federated data, using Arrow-native execution to make remote sources feel local. We think this is going to be especially important as agents query disparate systems and want to avoid scattering data fetching logic. -Under the hood, RivetDB is built in Rust and powered by [Apache DataFusion](https://datafusion.apache.org/). The combination gives us strong safety guarantees, solid performance, and a proven execution engine that plays well with Arrow. +Under the hood, RivetDB is built in Rust and powered by [Apache DataFusion](https://datafusion.apache.org/), providing strong safety guarantees, great performance, and a solid execution engine that plays well with Arrow. RivetDB is under active development, and the APIs will continue to shift as we move toward a stable 1.0 release. @@ -64,9 +64,9 @@ This foundation supports the larger roadmap described below. RivetDB aims to become a unified query engine that eliminates challenges working with between disparate data systems. The project emphasizes: - A consistent SQL interface for structured, semi-structured, and remote data sources +- Millisecond startup times for on-demand ephemeral compute - Intelligent caching that adapts to query patterns and reduces data movement - Tooling that gives developers introspection into data, metadata, and performance -- Millisecond startup times for on-demand ephemeral compute - Developer-friendly documentation and APIs The long-term goal includes distributed caching, additional connectors, real-time introspection, and seamless orchestration integration. @@ -91,9 +91,6 @@ These features define the first stable preview of RivetDB: - **Query Metadata API** Expose information about query execution: planning, caching, durations, and more. -- **Optional Session IDs** - Support optional sessions for multi-query workflows. - - **Table Caching Support** Enable caching of entire remote tables for repeated or incremental queries.