starrocks VS duckdb

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

I think you're talking about doing denormalization before importing data into an OLAP system to avoid subsequent joins. However, this greatly limits the flexibility of data modeling. Moreover, denormalization can be a headache-inducing process. In fact, I have tested StarRocks (https://github.com/StarRocks/starrocks), and it is capable of performing joins while streaming data imports, and the speed is very fast. It's worth giving it a try.

https://github.com/apache/doris Is a great example. Same for it's cousin https://github.com/StarRocks/starrocks that was an early fork of the doris project.

To be fair, these are the only examples I can think of and I only learned of these as I'm standing up new data infra using starrocks.

ClickHouseClickHouse and Starrocks are similar. They are both columnar databases powered by vectorization tech, which means they are really fast.

StarRocks, it’s a Linux Foundation project now, but a lot of the initial team and community behind it came from China.

https://github.com/StarRocks/starrocks

Funny that I hadn’t heard of them in the database space till they showed up at the top of ClickBench. Makes me wonder what other interesting projects I’m missing out on in China.

Full disclosure - I work for StarRocks (starrocks.com)

First of all, this is great. Transparent and healthy competition is always great for the customers!

Regarding the joined table queries that are missing in the tests, this is exactly why we built StarRocks - to give people the best performance of complex analytics queries on both joined tables and single tables.

I encourage you to checkout this blog: https://starrocks.medium.com/starrocks-outperforms-clickhous...

And, give us a star if you think we are doing the right thing: https://github.com/StarRocks/starrocks

Follow us on LinkedIn for the latest updates: https://www.linkedin.com/company/starrocks

I'm not sure if the fix is reassuring or not: https://github.com/duckdb/duckdb/pull/9411/files

It's an interesting question!

The problem is that the data is spread everywhere - no choice about that. So with that in mind, how do you query that data? Today, the idea is that you HAVE to put it into a central location. With tools like Bacalhau[1] and DuckDB [2], you no longer have to - a single query can be sharded amongst all your data - EFFECTIVELY giving you a lot of what you want from a data lake.

It's not a replacement, but if you can do a few of these items WITHOUT moving the data, you will be able to see really significant cost and time savings.

[1] https://github.com/bacalhau-project/bacalhau

[2] https://github.com/duckdb/duckdb

[4] Switch to Push-Based Execution Model by Mytherin · Pull Request #2393 · duckdb/duckdb (github.com)

it depends on your query obviously.

In general, I did very deep benchmarking of pg, clickhouse and duckdb, and I sure didn't make stupid mistakes like this: https://news.ycombinator.com/item?id=36990831

My dataset has 50B rows and 2tb of data, and I think columnar dbs are very overhiped and I chose pg because:

- pg performance is acceptable, maybe 2-3x times slower than clickhouse and duckdb on some queries if pg is configured correctly and run on compressed storage

- clickhouse and duckdb start falling apart very fast because they specialized on very narrow type of queries: https://github.com/ClickHouse/ClickHouse/issues/47520 https://github.com/ClickHouse/ClickHouse/issues/47521 https://github.com/duckdb/duckdb/discussions/6696

This action installs duckdb with the version provided in input.

Duckdb: https://github.com/duckdb/duckdb - seems pretty popular, been keeping an eye on this for close to a year now.

The Parquet-Go library is very complex, not yet success to use it. So I ask whether DuckDB can provide API https://github.com/duckdb/duckdb/issues/7776