topic Summary Indexing vs. Data Model Acceleration - which is more performant? in Knowledge Management

Summary Indexing vs. Data Model Acceleration - which is more performant?

simpkins1958 — Thu, 04 Jan 2018 22:26:40 GMT

I am trying to optimize searches that have large time spans (6+ months) with 10,000,000's of events. Which is more performant? Summary indexing or Data Model Acceleration? Conceptually I believe they would be similar in performance.

Re: Summary Indexing vs. Data Model Acceleration - which is more performant?

ddrillic — Fri, 05 Jan 2018 00:43:22 GMT

I like a lot the Summary Indexing feature and for any heavy duty app we set the Summary Indexing as a foundation. The set up of the feature is completely transparent to you as an admin fellow, meaning, you control every aspect of it and you can validate it. Now I'm not sure how Data Model Acceleration internally is being set up.

Re: Summary Indexing vs. Data Model Acceleration - which is more performant?

nikita_p — Fri, 05 Jan 2018 07:32:13 GMT

Hi @simpkins1958,
I think for your usecase summary index would be preferable because in splunk docs http://docs.splunk.com/Documentation/Splunk/7.0.1/Knowledge/Acceleratedatamodels, it is mentioned that If you always plan to run a report over time ranges that exceed the past 7 days, but don't extend further out than 30 days, you should select a Summary Range of 1 month when you set up data model acceleration for that report.
And in your case your searches have large time spans (6+ months).