Thanks for the education on MemSQL. I wasn’t aware of the analytics use case (had never come up in discussions I was a part of for that tech), so it was news to me.
This article had a nice overview. Somewhat outdated but mostly still up to date. https://lnkd.in/g4anCf5
I’ll say it seems precarious to me to mix and match row store in memory data with a columnar store. Is it never a performance issue to have these two systems potentially in contention with one another for resources?
Re:New in PostgreSQL 10
by manigandham on Friday September 22, 2017 @01:25PM
(#15314054)
It's just data in memory. Rowstores are read from memory and columnstores are read from disk. The architecture uses leaf nodes and aggregator nodes so aggregrator memory is used for assembling the final results of a query.
Version 6 is even faster, you can try out the beta: http://www1.memsql.com/beta-6.3-features.html
BigQuery streaming ingest also uses in-memory buffering into BigTable until it's written to disk, just like Cassandra with memtables flushed into on-disk SSTables.
Citus is more manual work than MemSQL and doesnt support columnstores native, although you can use it with their cstore extension to get both. It's just a different design giving you a postgres database that automatically shards vs MemSQL's many optimizations around HA, replication, and very fast analytics performance.
Try the features page: http://www.memsql.com/features/