VMware expands Redis open source in-memory data store programming options

The Redis in-memory data store update adds support for scripting and bit-wise operations

Redis, an open source in-memory data store maintained by VMware, has been upgraded to be more stabile and make more judicious use of memory, two traits that should make it more appealing for enterprise deployments.

"Redis 2.6 is more mature than Redis 2.4 in many ways, and users will have a better overall experience," said Salvatore Sanfilippo in an email interview. Sanfilippo is a VMware open-source developer who authored Redis.

"We already see that Cloud Foundry users love Redis for its simplicity of use. We anticipate this will only increase with Redis 2.6," Sanfilippo wrote, referring to how VMware offers the data store as part of its Cloud Foundry PaaS (platform as a service) offering.

One of a growing number of NoSQL databases, Redis is an advanced key store, one that can accept keys in a wide range of formats, including strings, hashes, lists and other formats. Because of the unique trait, Redis allows complex operations to be executed on the server, minimising the workloads on less-efficient clients.

"Redis is particularly suited for tasks where there is a very high load in general, and especially for very write-heavy workloads, where the data set size is in a range suitable to be stored in-memory," Sanfilippo wrote. "Because the Redis data model is different and exposes an API to manipulated fundamental data structures, there are problems that are simpler to model with Redis."

One job that Redis is particularly well suited for is real-time analysis of data, Sanfilippo said. The Redis data store, which is usually run entirely in memory, can easily work in conjunction with another on-disk data store that would hold a much larger collection of data.

"Just as PostgreSQL was the basis for so many leading analytic relational DBMS', Redis is being adapted for a variety of NoSQL-style products," said database industry analyst Curt Monash. In addition to real-time analysis, Redis is also frequently used as a caching layer, like "memcache on steroids," Sanfilippo said, and even as a messaging system. "Both types [of applications] depend on writing data quickly into simple data structures," Monash added.

The new features with the Redis 2.6 release offer a wider range of capabilities to help in these duties. For this release, significant parts of the Redis core engine were rewritten.

Hadoop gets a Real-Time Processing by Open Source vets

Nodeable solves real time Big Data issues

Big Data is certainly on a lot of people's lips these days. There is no doubt that we are certainly generating lots of data. Analyzing that data and making it useful is fueling literally millions of dollars of investment in companies around Hadoop, NoSQL, etc. One area where Big Data has some challenges is real-time analysis. With all of that data, analyzing in real time to get actionable intelligence into the hands of users is a big challenge. That is the the challenge that Nodeable is seeking to tackle.

Nodeable is led by a couple of open source veterans. Dave Rosenberg, formerly of Mule Source among a few other open source projects, is the CEO of Nodeable. With him are several folks who have worked with him in his previous open source companies. Additionally, Matt Assay, another veteran open source company builder, is on board at Nodeable as well.

I had a chance to sit down with Dave and talk about what he and his team are doing with Nodeable. You can listen in on our 15 or so minute conversation below. Let me warn you, the audio is a bit uneven at some points, but it isn't too bad and I think the quality of the conversation is well worth the problem with the quality of the audio.

The Nodeable team is using an open source program called Storm, which was originally developed by some folks at Twitter. Nodeable is seeking to commercialize this and build on top of it. This is a model that Dave has followed in the past and has lots of experience with.

Nodeable has been kicking around for a while now, but only recently really went public with this model. It is not competitive with Hadoop or other Big Data solutions, rather it brings another needed facet of Big Data to analytics.

So have a listen to Dave and check out a new and different Big Data solution coming to market.

Apache announced Cassandra NoSQL Database 1.1

The Apache Software Foundation (ASF) announced the release of Apache Cassandra 1.1, the highly scalable open-source distributed database.

Cassandra 1.1 handles massive data sets across community machines, large server clusters and data centers without compromising performance, and it does so running in the cloud or partially on-premise in a hybrid data store. Apache Cassandra 1.1 delivers improved caching, revised query language (CQL–Cassandra Query Language–a subset of SQL), storage control, schema/structure, Hadoop integration/output, data directory control and scalability.

"Apache Cassandra is the leading scalable NoSQL database in terms of production installations—the 1.0 release was a huge milestone," said Jonathan Ellis, vice president of Apache Cassandra, in a statement. "Version 1.1 improves on that foundation with many features and enhancements that developers and administrators have been asking for."

ASF officials said Cassandra is gaining attention as a best-of-breed "NoSQL" solution for its ease of use, powerful data model, enterprise-grade reliability, tunable performance and incremental scalability with no single point of failure. Cassandra accommodates high query volumes at high speed (sub-millisecond writes) with low latency, and handles petabytes of data across formats and applications in real time.

As it can handle thousands of requests per second, Apache Cassandra is deployed at a wide variety of enterprises, including Adobe, Appscale, Appssavvy, Backupify, Cisco, Clearspring, Cloudtalk, Constant Contact, Digg, Digital River, Expedia, Formspring, IBM, Mahalo.com, Morningstar, Netflix, Openwave, OpenX, Palantir, PBS, Plaxo, Rackspace, Reddit, RockYou, Shazam, SimpleGeo, Spotify, Twitter, Urban Airship, U.S. government agencies, Walmart Labs, Yakaz and more.

The ASF said the largest Cassandra production cluster to date exceeds 300 terabytes of data over 400 machines.

"The v1.1 release shows how rapidly Apache Cassandra has matured,” Patrick McFadin, chief architect of Hobsons, which offers CRM solutions to the education market, said in a statement. “The focus has clearly shifted to usability which is the sign of a solid system. I look forward to getting it into production right away. With features like Row-level isolation and Composite keys, Apache Cassandra v1.1 is really addressing user-driven needs with innovative solutions. Well done to all contributors for making this a great release."

Red Hat and 10gen Create Compelling Open Source Data Platform

Red Hat announced a partnership with 10gen as the first NoSQL database solution for its OpenShift PaaS offering in 2011. As enterprises increasingly look for proven solutions to handle big data needs, Red Hat and 10gen have broadened their collaboration around NoSQL, helping developers to deliver on the promise of big data, Internet and cloud technologies working with Red Hat solutions.

"Web and enterprise developers need solutions that allow them to rapidly deploy applications that deal with large amounts of data in flexible public or private cloud environments," said Scott Crenshaw, vice president and general manager, Cloud Business Unit at Red Hat. "Combining Red Hat's technology stack with 10gen's MongoDB NoSQL database will help developers to deliver on the promise of big data and cloud technologies."