ruw1090

No tax on tips does not apply to payroll taxes (FICA).

The Xenomorph term wasn't created by the fandom. It was first used in-universe in "Aliens".

Citation?

Sure, but given multiple opportunities (every time the clip gets brought up) to condemn it, he hasn’t. This should tell you enough.

Close, but in database years it was actually already in its mid life crisis.

The snowflake clusters are several factors bigger (and more expensive) than almost all of the comparison points.

That makes sense, thanks for clarifying. I got confused by the UI.

Do you have any benchmark results with Clickhouse in a clustered configuration (and other db's)? Is Clickhouse expected to be run in only single node deployments?

Yea, Redshift looks like it was run on an ra3.xl (4 cores) and is comparing against clickhouse on a c6a.4xl (16 cores). I suspect if this were normalized Redshift would have an edge.

There's a lot more involved in an execution engine running complex queries that are not single table group by than just QO (though this is important). It includes things like join implementations and associated optimizations, shuffle performance (which is important even for single table queries as you scale), etc.

The total estimated cost has increased by 44 Billion. Only ~10 billion has been spent on the project so far.

I stopped reading at "Incredibly, the state has not laid a single mile of track" for California High Speed rail, which is completely false. There are 119 miles under active construction and they've been putting down track since 2018.

> You are correct however that TimescaleDB requires more storage than some of these other options. If storage is the most important criteria for you (ie more important than usability or performance), then again I would recommend you to one of the other databases that are more optimized for compression. However, you can get 6-8x compression by running TimescaleDB on ZFS today, and we are also currently working on additional techniques for achieving higher compression rates.

This is a weird answer since compression is used by columnar databases like MemSQL and Clickhouse to both save on storage and accelerate queries. Compare this to using a generic a filesystem compression which would both compress worse and make the system slower.

I mean that an operation that needs more memory than is available will fail, but the server itself will remain operational. An simple example would be loading more data into an in-memory table (row store) than there is available memory. If you're using the columnstore then your storage won't be limited to memory.