We’ve added the following new SQL Function to the InMemory.Net database. Wanted to thank Jônatas Hudler for the suggestion. Substring(someString, startPos) Ascii(someChar) – Returns the ASCII code for a given char – or the first char, in case of a char array (string) Char(number) – Returns a char from an ASCII code Reverse(someString) – Reverse character positions of the given…

We have deployed 2 changes that should improve performance in InMemory.Net Index Creation Indexes between tables should now be created at least 5 times faster than before. Constant Expression Refactory If you have an expression that involves multiple constants, or has constants involved in a series of functions, InMemory.Net will now evaluate that constant one time only, and avoid recalculating it…

We recently released an updated version of InMemory.Net that runs on Mac OS C and Linux. Using the latest version of  Mono , we were able to get InMemory.Net up on these platforms. Currently we provide a zip of the relevant InMemory.Net files that can be extracted. The relevant InMemory.Net programs can then be run by prefixing mono before the name…

Here are two case studies of previous clients that have benefited from InMemory.net: Homestore & More are an Irish based chain of stores selling a huge number of home and garden products. All this data was being run on an SQL server and their reporting might have taken them considerable amount of time with each query taking up to 30…

Its been two years, a lot of caffeine, and finally we begin to officially unveil the new inmemory.net database. It works. Battletested with several existing clients, the new inmemory.net reporting database speeds up query times by an order of magnitude or more. Here’s the initial pitch: Inmemory.net delivers enterprise level speed at cost accessible to small and medium sized businesses.…

Our technology, powered by Dot Net, extracts data via an ODBC, OLEDB or Dot Net Data Provider source into an In-Memory Database. Data is compressed by a factor of 5-10. Typically the extract is saved to disk, then loaded into memory for ultra-quick retrieval purposes. SQL queries are used to aggregate possibly hundreds of millions of rows in under a second.