go-mysql-server VS tidb

We implemented a query optimizer with a flexible intermediate representation in pure Go:

https://github.com/dolthub/go-mysql-server

Getting the IR correct so that it's both easy to use and flexible enough to be useful is a really interesting design challenge. Our primary abstraction in the query plan is called a Node, and is way more general than the IR type described in the article from OP. This has probably hurt us: we only recently separated the responsibility to fetch rows into its own part of the runtime, out of the IR -- originally row fetching was coupled to the Node type directly.

This is also the query engine that Dolt uses:

https://github.com/dolthub/dolt

But it has a plug-in architecture, so you can use the engine on any data source that implements a handful of Go interface.

Might be interested in https://github.com/dolthub/go-mysql-server, which also does this

https://github.com/dolthub/go-mysql-server

One item under "Scope of this project":

Provide a runnable server speaking the MySQL wire protocol, connected to data sources of your choice.

I just wanted to say thanks for https://github.com/dolthub/go-mysql-server

This is incredibly useful for anyone who wants to build their own DB or wrap another datasource so it's queryable via MySQL protocol.

a very cool project they also maintain is a MySQL server framework for arbitrary backends (in Go): https://github.com/dolthub/go-mysql-server

You can define a "virtual" table (schema, how to retrieve rows/columns) and then a MySQL client can connect and execute arbitrary queries on your table (which could just be an API or other source)

Thanks for this write up! I've been really interested in postgres compatibility in the context of a tool I maintain (https://github.com/mergestat/mergestat) that uses SQLite. I've been looking for a way to expose the SQLite capabilities over a more commonly used wire-protocol like postgres (or mysql) so that existing BI and visualization tools can access the data.

This project is an interesting one: https://github.com/dolthub/go-mysql-server that provides a MySQL interface (wire and SQL) to arbitrary "backends" implemented in go.

It's really interesting how compatibility with existing protocols has become an important feature of new databases - there's so much existing tooling that already speaks postgres (or mysql), being able to leverage that is a huge advantage IMO

tidb has been around for a while, it is distributed, written in Go and Rust, and MySQL compatible. https://github.com/pingcap/tidb

Somewhat relatedly, StarRocks is also MySQL compatible, written in Java and C++, but it's tackling OLAP use-cases. https://github.com/StarRocks/starrocks

It's MySQL-Compatible database for scale and real-time analytics https://github.com/pingcap/tidb

PingCAP | https://www.pingcap.com | Database Engineer, Product Manager, Developer Advocate and more | Remote in California | Full-time

We work on a MySQL compatible distributed database called TiDB https://github.com/pingcap/tidb/ and key-value store called TiKV.

TiDB is written in Go and TiKV is written in Rust.

More roles and locations are available on https://www.pingcap.com/careers/

Pesquise por CockroachDB ou TiDB

OLTP usually comes with high throughput of transactions, which means usually write(e.g., IUD - insert, update, delete) to read (e.g., select) ratio is above 4 or 5 or even higher. There are some good benchmarks to test OLTP workload like TPC-C (https://www.tpc.org/tpcc/), and some benchmarks to test OLAP workload like TPC-H (https://www.tpc.org/tpch/). For mixed or hybrid OLTP and OLAP (it's called HTAP, see this blog for some background https://en.pingcap.com/blog/the-beauty-of-htap-tidb-and-allo...), TPC-H was originally designed for this, however, it actually doesn't reveal the real world workload with several drawbacks. A newer research work from UC Berkeley proposed a HTAP benchmark called TAOBench (https://www.vldb.org/pvldb/vol15/p1965-cheng.pdf) which is pretty interesting and worthy to check.

For the HTAP systems, as mentioned in the above blog, there are quite a few industrial products, like Google just announced AlloyDB (https://cloud.google.com/alloydb), Snowflake's UniStore (https://www.snowflake.com/workloads/unistore/), and one of the most popular open source projects TiDB (https://github.com/pingcap/tidb) which have been deployed by many business applications.

Hopefully these may help a little bit :-)