Live long in the memory?

Gridgain’s $10m funding gives in-memory credence

Chris Mayer
Gridgain-1

The latest funding for the Californian company comes at the ideal time, with the area of expertise expected to tiptoe to $1bn by 2016.

Just like Big Data, in-memory computing has been
hurtling towards the mainstream. The two areas dovetail each other
fairly well, as enterprises hunt for the quickest methods of
storing and processing data.

Several in-memory data grids, such as Pivotal’s
GemFire and Red Hat’s Infinispan, have gained traction in recent
times because of  their low latency, horizontal scalability
and greater reliability, as data is stored in a distributed
cluster.

Another in-memory company, Gridgain, has this
week secured a

$10m Series B
round of funding, giving
credence to the recent rapid rise of the area of expertise. The
funding will be used to expand Gridgain sales and marketing effort,
as well as being used in product development

The firm, based in California, are predominantly
known for their Java-based analytics stack,
In-Memory
Computing platform
. This is split into two main
components.

In-Memory Compute Grid
(IMCG) is the
processing part of the operation, executing necessary algorithms.
GridGain provide essentially a souped-up version of MapReduce,
capable of sub-100ms computations.

Source:Gridgain


In-Memory Data Grid
(IMDG) provides the
storage in an extremely parallelized manner in memory, making it
possible to load terabytes of data at breakneck speed, thus tying
nicely into the needs of Big Data-consuming companies. The key
value store is capable of gobbling transactional and
non-transactional data.

The ability to query in real-time within IMDG
gives it a plus point over bog standard HDFS, giving the company a
distinct advantage and putting it firmly ahead of the curve. While
many Hadoop vendors have recognised that HDFS’s speed isn’t up to
scratch, some customers may not be willing to wait for new projects
to shore up and mature to give Hadoop a much-needed
boost.

Curiously, Gridgain also provide finely-tuned
plugins for Hadoop and MongoDB, with he Hadoop accelerator alone
promising a 10x speed boost. Users can even snapshot data within
the framework.

The company boast some impressive clients using
the analytics solutions, with the likes of Sony, TomTom and Cisco
Systems all using Gridgain technology in production. GridGain was
founded by Nikita Ivanov and Dmitriy Setrakyan in 2007, and the
latest funding round takes the firm’s total investment to
$12.5m.

Massimo Pezzini, VP and Fellow at software
analyst Gartner believes that “In-memory will have an industry
impact comparable to web and cloud.”

The
global analyst predicted
back in April that,
although the in-data memory grid market is still its infancy, it
will be worth $1 billion by 2016. Leaders of the sector SAP are
even bolder, betting that their
HANA
database
will be generate as much cash on its own.
With Gridgain’s latest investment, it’s become even clearer that
in-memory data grids are set to become a critical part of the
enterprise infrastructure in the next two to three years.

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