Re: Vertica targeting PostgreSQL users
От | Peter Geoghegan |
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Тема | Re: Vertica targeting PostgreSQL users |
Дата | |
Msg-id | CAH2-WznyX9fkPEiWJRRRUh0_1OthKsZZ6ficjRDo8rci+R6wYA@mail.gmail.com обсуждение исходный текст |
Ответ на | Vertica targeting PostgreSQL users ("Jonathan S. Katz" <jkatz@postgresql.org>) |
Ответы |
Re: Vertica targeting PostgreSQL users
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Список | pgsql-advocacy |
On Mon, Nov 20, 2017 at 7:43 AM, Jonathan S. Katz <jkatz@postgresql.org> wrote: > Vertica current marketing is heavily targeting Postgres users: > > https://www.vertica.com/postgresql/ > Going forward, we must continue to understand our users’ needs while > ensuring that we can provide them as many resources as possible to help them > manage Postgres and show them that here is great help available when it is > required. I noticed this quote, which was fairly prominently placed: "PostgreSQL just isn’t designed to do analytic-type queries. Those are big aggregations, and Postgres, even though it is a great relational database, is really tailored for single-record lookup." Isn't the latter sentence really quite fair? It seems unwise to try to compete with a dedicated MPP column store solution like Vertica. Of course it's going to be much better at Postgres for a use-case that is truly within its niche. That said, I definitely think that systems like Vertica could easily get users due to the extremely simplistic, over-confident thinking that many people display around scalability. For some reason, I've met a number of people that believe that using Postgres somehow becomes untenable once you reach 1TB of data. Ideas like this imbed themselves by being simple, and getting repeated without being challenged. People think they need a column store, or something like Cassandra, when in fact they need to do some performance triage using pg_stat_statements, rethink backups, and maybe upgrade hardware. The lesson for us, as people that want to do better advocacy, may be that we need to counter these preposterous rules of thumb with simple counter examples. For example: I can restore the entire stack overflow databases on my laptop; it contains all stack overflow posts, ever, and comes in at approximately 100GB, including basic indexes. The largest table can have an index created on it in a couple of minutes on my machine that weighs less than 2KG, as we see here: https://blog.anayrat.info/en/2017/11/19/postgresql-10--icu--abbreviated-keys/ The actual stack overflow production database runs on a single SQL Server node, and does come in at 2 - 4 TB IIRC, because they have event data too, but the fact remains that you essentially get all of stack overflow in a ~100GB Postgres database. Many users have no idea how far a traditional monolithic relational database can scale without much difficulty, because they measure the wrong thing -- the thing that is easiest to measure. -- Peter Geoghegan
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