Compression Delay

Rob Farley digs into Compression Delay as part of real-time operational analytics:

The thing with Operational Analytics is that the analytical data, reporting data, warehouse-style data, is essentially the same data as the transactional data. Now, it doesn’t look quite the same, because it’s not been turned into a star-schema, or have slowly changing dimension considerations, but for the purposes of seeing what’s going on, it’s data that’s capable of handling aggregations over large amounts of data. It’s columnstore.

Now, columnstore data isn’t particularly suited to transactional data. Finding an individual row within columnstore data can be tricky, and it’s much more suited to rowstore. So when data is being manipulated quite a lot, it’s not necessarily that good to be using columnstore. Rowstore is simply better for this.

But with SQL 2016, we get updateable non-clustered columnstore indexes. Data which is a copy of the underlying table (non-clustered data is a copy – clustered data or heap data is the underlying table). This alone presents a useful opportunity, as we can be maintaining a columnstore copy of the data for analytics, while handling individual row updates in the rowstore.

Read the whole thing.

Related Posts

T-SQL Tuesday Roundup

Arun Sirpal has the T-SQL Tuesday roundup for January 2018: Thank you to everyone that took the time to write and contribute, I enjoyed reading about how you conquered your challenges, here is a round-up in no particular order. There is, as always, plenty of reading available.

Read More

T-SQL Tuesday Roundup

Mala Mahadevan has the roundup for this month’s T-SQL Tuesday: Thank you to all of you for taking time to contribute. I like the suggestion made by Glenda Gable on being partners to help with accountability on our goals. If anyone feels up to this just leave a comment below, we can set up a […]

Read More

Categories

August 2016
MTWTFSS
« Jul Sep »
1234567
891011121314
15161718192021
22232425262728
293031