Yeah, and that list can be broken down almost infinitely. For example:
* faster to query data using exact match on multiple fields
* faster to query data using fuzzy match, wildcard match, date range match,
etc.
* faster to query data joining five tables
* faster to query data with very large (or wide) records
* faster to query data with very large result set
* faster to query data using full-text search with phrase matching
* faster with all of the above in a single query
As I'm sure you know, there are may other ways to compare databases that might
align better with tangible value:
* are there core features that would benefit the application and clearly
differentiate the databases?
* search
* faceted search
* tunable relevance ranking
* fuzzy matching to de-duplicate customers across systems despite
name misspellings
* schema flexibility
* since CRM benefits from integrating data from many sources
* since tradestore data formats change
frequently<http://www.marklogic.com/blog/nosql-operational-trade-store/>
* is there any impedance mismatch between persistence data model and
application data model?
* does the trade-store require any advanced server-side rules at index time
/ query time?
* if so, are there features that will help implement those rules
* etc., etc.
Sam Mefford
Senior Engineer
MarkLogic Corporation
[email protected]<mailto:[email protected]>
Cell: +1 801 706 9731
www.marklogic.com<http://www.marklogic.com>
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On 5/18/2016 9:28 AM, Anthony Coates wrote:
Classification: Public
Hi. I'm not allowed to make technology recommendations, and so I'm not going
to recommend any particular database here.
However, historically many database vendors have been uncomfortable with people
publishing benchmark comparisons, because the actual performance of a database
often depends on exactly how you use it. Sometimes you may be hitting the
sweet spot of a particular database, sometimes you may not be, and the database
that is faster for you might not be the database that is faster for someone
else.
There are also different ways to measure "faster":
* faster to store data
* faster to query data
* faster to develop/test/debug applications (i.e. "faster to market").
All of those can be important, but in different cases a different one may be
the most important. So, if you can define which area of database performance
or use is the most critical one to be "faster" for your use case, it might be
easier for you to make a clear statement about how your short-listed databases
compare to each other for your own needs.
Cheers, Tony.
-----Original Message-----
From:
[email protected]<mailto:[email protected]>
[mailto:[email protected]] On Behalf Of Sebastien Vige
Sent: 18 May 2016 16:14
To: [email protected]<mailto:[email protected]>
Subject: [MarkLogic Dev General] Banking - ml vs ms sql (or oracle) |
performance story
Team,
We are battling with a dev team. We need to show them ML is faster than MSSQL.
In which user story (banking or other) can we reference / present a factual
performance gain ?
This will help us to convince our prospect.
Our use cases are CRM web app fueled by ML as well as a mini tradestore.
Any input welcome !
Tx
Seb
Kind Regards
Sebastien
Envoyé de mon iPhone
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