151–160 of 173 posts
As I already said or rather asked there: Assume I already use Clickhouse for example. What are the benefits of QuestDB? Why should I use it instead?
Surely it's a good tech and competition is key. But what are the key points that should make me look into it? There is a lot of story about the making and such, but I don't see the "selling point".
Am I the only one that's like "wtf is a time-series database compared to a normal one?"
- ingesting large amounts of data
- aggregating data around a "time" field (i.e. per minute, per hour, etc)
- updates are rare
- deletes are rare
By sacrificing update and delete functionality, timeseries DB's can optimize creating and reading records.
> https://news.ycombinator.com/item?id=22803504 As I already said or rather asked there: Assume I already use Clickhouse for example. What are the benefits of QuestDB? Why should I use it instead? Surely it's a good tech and competition is key. But what are the key points that should make me look into it? There is a lot of story about the making and such, but I don't see the "selling point".
Ultimately as a result we think that questDB will be a better fit for your community. We acknowledge that Clickhouse has lot more features as of now being a more mature product.
Impressive. Can we talk?
One question, there are many open source database startups that make it easy to scale on the cloud. However, when you look into the offering, the scaling part is never actually open source and you end up paying for non open source stuff just like any other proprietary database. So I guess my question is, are you planning to go open core too or will you remain open source with some SaaS offering? Good luck to you!
2. If so, can you give some performance figures for a single machine and reasonable scale factors (10 GB, 100 GB, 1000 GB)? Execution times for single queries are even more interesting than the overall random-queries-per-hour figure.
3. Can you link to a widely-used benchmark for analytic workloads on time series, which one can use to compare performance of various DBMSes? With SQL-based queries preferably.
There's an opportunity for a tool that combines this sort of technology in the backend with a spreadsheet-like GUI powered by formulas and all the user friendliness that comes with a non-programmer interface. Wall Street would forever be changed. Source: I'm one of the poor souls fighting my CPU and RAM to do the same thing with Excel and non-native add-ins by {FactSet, Capital IQ, Bloomberg} This stuff SELECT * FROM…
We can add a connector for QuestDB if someone is really interested in this.
Congrats on the launch! One question, there are many open source database startups that make it easy to scale on the cloud. However, when you look into the offering, the scaling part is never actually open source and you end up paying for non open source stuff just like any other proprietary database. So I guess my question is, are you planning to go open core too or will you remain open source with some SaaS offerin…
To answer your question, it will depend how big of a scale we are looking into. If you are a large company running questdb throughout the organization and need a specific feature set to do so, you will probably be looking to get our paid offering.
Earlier quoted context omitted.
One differentiating feature is "as of" join. You have records of the form (time, value), and you ask "what's the most recent value as of $time?"; On a non-TS oriented DBMS, this query is usually slow and hard to write. Window extensions to SQL can make it a little better, but - you can assume that a proper TSDB answers this query x10 to x10,000 times faster on the same hardware, especially when done in bulk (e.g.: I…
> On a non-TS oriented DBMS, this query is usually slow and hard to write. I don't see why this is hard to write: SELECT max(time) as most_recent_time, transaction_price INTO newtable FROM oldtable WHERE time > $my_datetime GROUP BY time; As for being slow - can you provide some references about this being slow in non-time-series columnar DBMSes? MonetDB, Vectorwise, Vertica?
I don't understand your query - max(time) .. GROUP BY time means that every record is its own group, so max(time)==time; also, you will have a result for every single point in time after the requested time.
There is no way in standard SQL (without window extensions) to do this with just one clause; you need the price associated with the min(time) associated with time>=$my_datetime ; You need either a subquery, a join, or some other correlated query. e.g.
SELECT time, price FROM trades WHERE time IN (SELECT min(time) FROM trades WHERE time>=$my_datetime)
And that's for one record; It gets more complicated when you try to do a batch.
> As for being slow - can you provide some references about this being slow in non-time-series columnar DBMSes? MonetDB, Vectorwise, Vertica?
I've timed kdb2 against Vertica a decade or so ago, and kdb2 was about x10 faster, I didn't do a proper benchmark but monetdb was in the x10-x100 slower than kdb2 at the time.