Mari­aDB to launch in­no­va­tion re­search labs

OpenSource For You - - Foss Bytes -

Mari­aDB is launch­ing a re­search divi­sion, called Mari­aDB Labs.

With this, the open source data­base com­pany will tackle the most press­ing is­sues in the data­base field. To be­gin with, it has col­lab­o­rated with In­tel on a new ref­er­ence ar­chi­tec­ture. Michael Howard, CEO, Mari­aDB, shared plans at the re­cently held

M18 user con­fer­ence in New York. He said that the labs will fo­cus on three key ar­eas—ma­chine learn­ing, dis­trib­uted com­put­ing, and the use and ex­ploita­tion of new chips, per­sis­tent stor­age and in-mem­ory pro­cess­ing.

“Our re­search col­lab­o­ra­tion with Mari­aDB will fo­cus on an in­no­va­tive dis­trib­uted log ar­chi­tec­ture us­ing In­tel Op­tane SSDs and In­tel Per­sis­tent Mem­ory wo­ven to­gether through high-per­for­mance fab­rics,” said Alper Ilk­ba­har, In­tel VP, data cen­tre group; and GM, data cen­tre mem­ory and stor­age so­lu­tions.

The col­lab­o­ra­tion will look into a new ref­er­ence ar­chi­tec­ture for dis­trib­uted data­bases us­ing high­per­for­mance fab­rics. “Our shared goal is to en­able faster re­cov­ery and cloning, in­crease over­all per­for­mance and re­silience, and re­duce so­lu­tion TCO from to­day’s level,” elab­o­rated Ilk­ba­har.

In terms of ma­chine learn­ing, Mari­aDB Labs will be tasked with in­ves­ti­gat­ing how to use su­per­vised and un­su­per­vised tech­niques to drive bet­ter au­to­ma­tion, in­clud­ing self-con­fig­u­ra­tion and self-op­ti­mi­sa­tion when run­ning data­bases in the cloud. The re­search will look at dis­trib­uted com­put­ing, specif­i­cally im­prov­ing upon Web­scale, geo-dis­trib­uted de­ploy­ments. Last but not the least, Mari­aDB Labs will look to de­velop next-gen­er­a­tion chips, mem­ory and stor­age in a bid to re­think the un­der­ly­ing in­fra­struc­ture on which data­bases run.

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