I apologize, because I literally don't know, but have you used any of these solutions at the scale where there might be billions or trillions of rows in a table/collection? I'm currently using Mongo at that scale and would love to evaluate some alternatives.
If it helps for context, we have accepted that ad-hoc queries are not possible, and we have our own solution for searching.
TiDB has a similar case study: Queries over 1.3 Trillion Rows of Data Within Milliseconds of Response Time at Zhihu.com
https://pingcap.com/success-stories/lesson-learned-from-quer...
The latest stats in the same case scenario (already-read posts) Zhihu is:
- 2.6 Trillion Rows
- 560TB data
- 200 TiKV instances
Very cool! Thanks, I will look into it.
Re:MongoDB History
by manigandham on Tuesday September 08, 2020 @03:14AM
(#24405935)
We used MemSQL with 100s of billions of rows for years in production.
If you're working at that scale, it sounds like that's more of an OLAP use-case where MemSQL and other column-oriented databases would suit better than an OLTP document-store. Maybe you can share more details for better recommendations.
If still want a document-store then RavenDB is a great choice with proper clustering, full-text search, SQL-like querying, graph queries, etc. ArangoDB is also good choice.