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covalenthq.com4 pointsby gane5h2 comments
* the ingest-side can be scaled up by adding more shards
* the query-side can be scaled up by adding more replicas
To compute rollup analytics, we make heavy use of Elasticsearch's aggregation framework to compute daily/weekly/monthly/quarterly active users. - how complete is the postgres functionality (e.g.: lateral joins)
- can you set a sharding key to control the shard distribution
- does the database do multiple passes for queries with subselects
- usually one increases the replication factor (limited by budget) to improve query times, with the limitation that it slows down loading time. does the DB stage intermediate writes to batch them, so does the user need to do this? this works really well for append-only, timestamped event data.
- do you have a job manager or scheduler, needed when you have multiple views that need to be updated without melting your infrastructure
- how easy is it to operate? does the database expose operational metrics so that you can see the load on each shard to potentially detect unbalanced shards?
- tips on hardware configuration (big advantage of redshift here is that you don’t have to run your own warehouse.) maybe partner with MongoHQ?
It’ll be nice to see some sample query plans graphically visualized.