Startup #Iguaz.io has unveiled a virtual (big) data services architecture which it says can deliver data in the needed firms to apps in the Big Data infrastructure without multiple and repeated data copying and conversion.
The company is a 2014-founded, $15m A-round-funded startup. Its pitch is that the entirety of the data supply workflows in the Big Data sphere are over-complicated and represent band-aid on band-aid.
What it says we need is something [cue marketing-speak] that consolidates data into a high-volume, high-velocity, real-time data repository design that virtualises and transforms data on the fly, exposes it as streams, messages, files, objects or data records consistently, and stores it on different memory or storage tiers.
Here is a diagram it has supplied, mentioning #Hadoop, #HBase, #Spark, #Splunk, #Kafka and #Redis, and showing the complexity which it says is endemic:
http://www.theregister.co.uk/2016/06/09/iguaz_big_data_startup/
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