21–30 of 54 posts
How does something like Tableau fit in? I know of people using Tableau with a Postgres connector, but I am not sure if that allows you the same kind of performance as you'd get with OLAP or even a columnar DB.
Tableau has a proprietary extract engine called Hyper that uses a sort of columnar storage. Then you can use the extract in dashboards.
I'm conflicted; its a nice write-up, and probably generally true right now, for most stuff. However, I still live with databases big enough to still need cubes, although these cubes can afford to be less refined these days. Saying 'bigtable can do a regex on 30M rows per second' isn't saying it can't be done cheaper and quicker without paying google etc, if you just have some cubes. And I think its going to track the…
Would you view presto in its current state as a replacement for vanilla Postgres with FDW for standard data analysis queries? I don't fully understand the Postgres/Presto relationship.
Sorry, could someone ELI5 what is OLAP? And while you are there, what is Tabular Model? As background,I have worked with SQL and relational databases, and occasionally keep on hearing these, but nobody ever explained to me what these are and why I should be interested. So far I have just shrugged and thought that I guess my workloads/datamodels/whatnot just do not need these fancy things, but always I see them, there…
The kind of relational database you're familiar with is probably OLTP (Online Transactional Processing).
well, I would like to say the OLAP Cube is just re-rising now. There are 1000+ companies deployed Apache Kylin (OLAP Engine for Big Data) in the past 5 years, for 100+B rows, for 100+ concurrent users...many different use cases are based that technology...it works very well with BI tools and so friendly to analysts who are using such "old fashion" every day over the decade (how hard for them to be Data Scientists?) c…
If you want an alternative take on where OLAP is today and what it is capable of, I usually recommend this article: https://kyligence.io/blog/olap-analytics-is-dead-really/
This piece reiterates a bunch of the usual misunderstandings of OLAP. Likely because it’s following the DBMS community’s redefinition of OLAP towards cross-tab group-by, and away from the higher end of the OLAP market. The “cube” is just as much a logical construct as a SQL table is, and just because row stores were bad at certain analytics didn’t mean that SQL was. Compressed column-stores hurt OLAP, because update…
But why do you want high update throughout when you're doing mostly reads? Every definition I read about OLAP says this is one of the fundamental differences, or am I misunderstanding something?
Sorry, could someone ELI5 what is OLAP? And while you are there, what is Tabular Model? As background,I have worked with SQL and relational databases, and occasionally keep on hearing these, but nobody ever explained to me what these are and why I should be interested. So far I have just shrugged and thought that I guess my workloads/datamodels/whatnot just do not need these fancy things, but always I see them, there…
OLAP: Online Analytical Processing. Cranking through large amounts of data with a focus on aggregations like sums, averages, medians, etc. Measures (numbers) are defined by dimensions (attributes with usually discrete domains). Aggregations are frequently precomputed on many (or all) dimension axes so that they are immediately available. Models can be built from something as simple as a wide CSV file or as complicate…
I think the OLAP term has been around a long time, some OLAP tasks of the past are probably not so huge today, I wonder if the shrunked-by-time tasks are still called OLAP or if the smaller ones are implemented differently.
This piece reiterates a bunch of the usual misunderstandings of OLAP. Likely because it’s following the DBMS community’s redefinition of OLAP towards cross-tab group-by, and away from the higher end of the OLAP market. The “cube” is just as much a logical construct as a SQL table is, and just because row stores were bad at certain analytics didn’t mean that SQL was. Compressed column-stores hurt OLAP, because update…
> Compressed column-stores hurt OLAP, because update throughput (the “on-line” in OLAP) is relatively bad. Uncompressed / array stores are quite good. But why do you want high update throughout when you're doing mostly reads? Every definition I read about OLAP says this is one of the fundamental differences, or am I misunderstanding something?
I'm conflicted; its a nice write-up, and probably generally true right now, for most stuff. However, I still live with databases big enough to still need cubes, although these cubes can afford to be less refined these days. Saying 'bigtable can do a regex on 30M rows per second' isn't saying it can't be done cheaper and quicker without paying google etc, if you just have some cubes. And I think its going to track the…
Thanks for your comment, I'm not familiar with presto at all - but I did do a bit of reading of an older article: https://www.slideshare.net/frsyuki/prestogres-internals Would you view presto in its current state as a replacement for vanilla Postgres with FDW for standard data analysis queries? I don't fully understand the Postgres/Presto relationship.
In a way, presto is like a bunch of FDWs on steroids, and a query planner that has above average cost model for hive etc.
There are plenty of things that presto isn’t, such as a good replacement for Postgres in classic oltp workloads.
Sorry, could someone ELI5 what is OLAP? And while you are there, what is Tabular Model? As background,I have worked with SQL and relational databases, and occasionally keep on hearing these, but nobody ever explained to me what these are and why I should be interested. So far I have just shrugged and thought that I guess my workloads/datamodels/whatnot just do not need these fancy things, but always I see them, there…
All these reports can be kept up to date in a live fashion by the OLAP service as new relevant data comes in, much like a materialized view.
Many accounting systems support OLAP based queries in order for the accounting department to design reports and export them to excel.