datafuse VS greptimedb

v0.4.102-nightly

Datafuse is currently in Alpha and is not ready to be used in production, Roadmap 2021

v0.4.95-nightly

1. With the improvement of the rust ecosystem, using rust has made database development faster and easy, for example datafuse use the tokio to implement the pipeline https://github.com/datafuselabs/datafuse/tree/master/fuseque....

2. Couldn't agree with you more with easier-to-manage as a first-class feature, but some times easier-to-manage is built on stability, that's what datafuse is trying to do.

Datafuse – Modern Real-Time Data Processing in Rust\ (8 comments)

Datafuse even borrows code from datafusion, which makes the name choice seem intentionally confusing. https://github.com/datafuselabs/datafuse/issues/654

Datafuse - A Modern Real-Time Data Processing & Analytics DBMS with Cloud-Native Architecture, built to make the Data Cloud easy. Written in Rust.

GreptimeAI, built upon the open-source time-series database GreptimeDB, offers an observability solution for Large Language Model (LLM) applications, currently supporting both LangChain and OpenAI's ecosystem. GreptimeAI enables you to understand cost, performance, traffic and security aspects in real-time, helping teams enhance the reliability of LLM applications.

Continuing to work hard on a new MetricEngine in GreptimeDB. BTW, If you have a keen interest in Rust or database development, GreptimeDB might be a good starting point. Check it out for some good first issues here.

Since the very first day of GreptimeDB going open-source, it embraced the automated software building process with GitHub Actions, and leading to the inaugural Release Pipeline.

Born from the open-source project GreptimeDB, GreptimeCloud serves as a fully-managed, serverless cloud backend for Prometheus, offering integrated support for remote read/write protocols and PromQL as one of our primary query languages.

Recently, while working on our GreptimeDB project, we encountered an issue with calling asynchronous Rust code in a synchronous context.

To explore data stored in GreptimeDB through PromQL, GreptimeDB needs to provide the ability to parse the query into AST (abstract syntax tree), and retrieve data from memory or disk via logical and physical plans. Since there is no ready-to-use PromQL Rust Parser, our team decides to develop it by ourselves. We’re glad to announce that promql-parser v0.1.0 is now available.

This is truly a fantastic combination -- implement the logic in Rust and use it in Python. GreptimeDB also implements a similar functionality that allows writing Python script to do post-process of SQL query results, with the help of RustPython and Arrow. Maybe this combination can bring a sweet point between performance and efficiency.

docs: https://docs.greptime.com/user-guide/coprocessor-and-scripti...

code: https://github.com/GreptimeTeam/greptimedb/tree/develop/src/...