A few months ago, I spoke at the conference where I explained the difference
between caching and an in-memory data grid. Today, having realized that many
people are also looking to better understand the difference between two major
categories in in-memory computing: In-Memory Database and In-Memory Data
Grid, I am sharing the succinct version of my thinking on this topic - thanks
to a recent analyst call that helped to put everything in place
Skip to conclusion to get the bottom line.
Let's clarify the naming and buzzwords first. In-Memory Database (IMDB) is a
well-established category name and it is typically used unambiguously.
It is important to note that there is a new crop of traditional databases
with serious In-Memory "options". That includes MS SQL 2014, Oracle's
Exalytics and Exadata, and IBM DB2 with BLU offerings. The line is blurry
After five days (and eleven meetings) with new customers in Europe, Russia,
and the Middle East, I think time is right for another refinement of
in-memory computing's definition. To me, it is clear that our industry is
lagging when it comes to explaining in-memory computing to potential
customers and defining what in-memory computing is really about. We struggle
to come up with a simple, understandable definition of what in-memory
computing is all about, what problems it solves, and what uses are a good fit
for the technology.
In-Memory Computing: What Is It?
In-memory computin... (more)
by Abe Kleinfeld and Nikita Ivanov
Gordon E. Moore's famously predicted tech explosion was prophetic, but it may
have hit a snag. While the number of transistors on integrated circuits has
doubled approximately every two years since his 1965 paper, the ability to
process and transact on data hasn't. We're now ingesting data faster than we
can make sense of it, leaving computing at an impasse. Without a new
approach, the innovation promised by the combination of Big Data and internet
scale may be like the flying cars we thought we'd see by 2014. Fortunately,
this is is not the c... (more)
If you know anything about Hadoop architecture - the task seemed daunting to
us and it proved to be one of the most challenging engineering feat that we
have accomplished so far.
After almost 24 months of development, tens of thousands of lines of Java,
Scala and C++ code, multiple design iterations, several releases and dozens
of benchmarks later we have the product that can deliver real-time
performance to Hadoop with only minimal integration and no ETL required.
Backed-up by customer deployments that prove our performance claims and
validate our architecture.
Here's how we d... (more)
What are the performance differences between in-memory columnar databases
like SAP HANA and GridGain's In-Memory Database (IMDB) utilizing distributed
key-value storage? This questions comes up regularly in conversations with
our customers and the answer is not very obvious.
First off, let's clearly state that we are talking about storage model only
and its implications on performance for various use cases. It's important to
Storage model doesn't dictate of preclude a particular transactionality or
consistency guarantees; there are columnar databases tha... (more)