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by manigandham 2460 days ago
Those are still relational databases, just with column-oriented/column-store tables. I don't see how the storage layer changes the database type. For example, MemSQL has both rowstores and columnstores. Postgres 12 has pluggable storage with column-store (zedstore).
1 comments
shakkhar 2460 days ago
> I don't see how the storage layer changes the database type.

It does, because it leads to other types of optimization. LittleTable [0], for example, keeps adjacent data in time domain adjacent in disk. So querying large amount of data that are close to each other is efficient even on slow (spinning) disk. Vertica [1] does column compression which allows it to work with denormalized data (common in analytics workload) efficiently.

In an ideal world, you could have a storage layer sitting below a perfect abstraction; orthogonal to higher levels. In the real world, column-based and row-based are two completely different categories serving very different use-cases.

[0] https://meraki.cisco.com/lib/pdf/trust/lt-paper.pdf [1] http://vldb.org/pvldb/vol5/p1790_andrewlamb_vldb2012.pdf

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manigandham 2459 days ago
The underlying database type hasn't changed. LittleTable is a relational database (it's the first sentence in the paper). Vertica is also a relational database.

Stored is an implementation detail. Optimizations are improvements to performance. Neither affects the fundamental data model, which in relational databases is relational algebra over tuple-sets.

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jnordwick 2459 days ago
Timeseries is the data model and that is, for the upper end, synonymous with column-oriented. In my top comment, I mean timeseries/column-oriented (there are other series besiudes time, byt they fit the same data model).

The top TS databases are more than just storage too. You need a query language that can exploit the ordering column-oriented gives you that the row-oriented relational doesn't.

On the lower end (eg, Timescale db) trying to fit a timeseries model on a row-oriented architecture which is a poor fit.

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manigandham 2458 days ago
Time-series is definitely not synonymous column-oriented. The data model is separate from the storage layer which is separate from the use-case.

You're talking about relational databases (which is the formal type) designed for large-scale analytics using column-oriented storage and processing and supporting a time-series use-case.

Storage and querying just for time-series specifically is more about product features than the underlying type. For example, here's Pinterest doing the same on HBase: https://medium.com/pinterest-engineering/pinalyticsdb-a-time...

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