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In-memory databases: Use a standard product, or roll your own?

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In-memory databases: Use a standard product, or roll your own?

· Java Zone
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Check out this 8-step guide to see how you can increase your productivity by skipping slow application redeploys and by implementing application profiling, as you code! Brought to you in partnership with ZeroTurnaround.

Here are a few questions I would like to ask the community:

As memory gets cheaper, more and more application datasets can now be kept fully in memory, and just have changes flushed to disk. No reads from disk (except at startup) - only writes.

Some of the applications I think could benefit from having all data in memory, never to read from disk but only to flush changes to disk (async perhaps), are:

*) Multiplayer game server
*) Search engine live index
*) Live analysis systems

 

1) Have you had any experiences with this kind of setup? All data in memory for your application?

2) Did you use a standard database product?

3) If yes, which product did you use, and what were the benefits?

4) Did you end up just keeping the data as objects in memory, and create your own indexes etc. to search through it?

5) If yes, what are your experiences with that?

6) Does anyone have any speed comparisons?

 

I remember working for a data warehouse once that exported part of their index to KDB, an in memory lightning fast database. Indices were rebuilt every night, and remained unchanged for 24 hours. The speedup was x 1000 compared to searching in MS SQL Server back then (in 2001).

The Java Zone is brought to you in partnership with ZeroTurnaround. Check out this 8-step guide to see how you can increase your productivity by skipping slow application redeploys and by implementing application profiling, as you code!

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