The round includes contributions from Clustrix’ current backers Sequoia Capital, U.S. Venture Partners, and ATA Ventures.

“We have successful production environments running around the world with our appliance — so now the goal is to open up distribution to developers,” CEO Robin Purohit said in an interview. Towards that end, Clustrix recently made the new version 5.0 of its proprietary database available on Amazon Web Services. It’s already available on Rackspace, GoGrid, Equinix and BlueBoxGroup infrastructure.

Here’s how GigaOM’s  Stacey Higginbotham wrote about the initial launch in 2010:

Clustrix [claims] that it’s built a transaction database with MySQL-like functionality and reliability that can scale to billions of entries. Clustrix plans to sell its appliance (which consists of more than a terabyte of memory and its proprietary software) to web firms that don’t want to take on the complicated task of sharding their data (replicating it across multiple databases), or moving to less robust database options like Cassandra or a key value store such as what’s provided by Twitter.

Jesse Proudman CEO of BlueBox, one of Clustrix’s hosting partners, characterized Clustrix as a “‘fire and forget’ solution that takes care of driving scale within MySQL. Its core premise is unlimited scalability without having to build that logic into your application … [it] takes care of MySQL sharding internally.”

Clustrix competes most directly with dbShards if a customer really cares about MySQL compatibility and with NuoDB if they don’t, according to Curt Monash, president of Monash Research.

So when it comes to big-scale, Clustrix has a story to tell, but the market is flooded with rivals. Still, it doesn’t help that the overall cloud database category will be under the microscope given that Xeround, a  MySQL startup, is shutting down this week, as GigaOM first reported on May 1.

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ParElastic sits in between the application and the underlying database and lets developers scale without having to resort to complicated sharding or maybe even moving the database back in-house where they can run it on a bigger server. Architecturally, Founder and CEO Ken Rugg told me, ParElastic’s Database Virtualization Engine is similar to a parallel database system, although it functions more like middleware that manages multiple database instances as one and is designed for operational rather than analytic workloads.

Because it intelligently balances database load and distributed data across servers, ParElastic is ideal for multitenant situations where multiple users, applications or services are accessing the database simultaneously, Rugg added.

Now, anyone familiar with the next-generation database market might think they’ve heard this story before, and they kind of have. The NoSQL database movement rode into town on the promise of high scalability, and the NewSQL movement furthered that story by bringing scale-out performance to SQL. Some of these databases are even available as cloud services.

However, Rugg explained, there’s a big difference between these options and what ParElastic does. Namely, while NoSQL and NewSQL options require deploying an entirely new database and likely rewriting some application code, ParElastic’s software just overlays customers’ existing cloud databases. Rugg said about half of its early users are running standard MySQL versions on Amazon Web Services, while the rest are spread across cloud providers such as Rackspace, Joyent and LiquidWeb.

Some ParElastic users actually manage existing SQL services such as Amazon’s Relational Database Service and Google Cloud SQL. One even uses it to manage an in-house database environment. And technically, Rugg noted, ParElastic could manage cross-cloud database deployments but, because of the inherent latency hit that would entail, “we wouldn’t recommend that.”

However, he said, the biggest beneficiary of ParElastic aside from the company itself might well be AWS. It is by far the most widely used cloud in the world, but when users reach the limites of their single database instances, Amazon usually tells them to look into sharding or perhaps transitioning to DynamoDB. “None of those are really too friendly for Amazon keeping their customers moving forward in their cloud,” Rugg said.

Further, although certain cloud providers offer better CPU, IO or network performance than AWS does (Rugg cited Rackspace as being particularly strong on IO performance, for example, and ProfitBricks as looking promising on the network front), “Amazon is sort of the lowest common denominator in a number of ways,” Rugg explained. The economics and performance requirements vary from application to application, of course, but ParElastic could help stitch together a number of commodity AWS instances to provide suitable performance at a lower cost than might be possible using the biggest, fastest instances from other providers.

Having watched the cloud market unfold as it has, though, Rugg and ParElastic aren’t banking on AWS — which has a reputation for launching services that compete with startup ecosystem partners — as the future of the business. By supporting other cloud providers that are gaining acceptance (aside from the ones Rugg noted, Google has been impressing some with the performance of its Compute Engine service), ParElastic is in a pretty good position to handle whatever cloud-database market shifts might occur.

“Even if Amazon comes out and says ‘We’re going to replace you with something we built back in the lab,’ that puts us in a great position in terms of validating the market,” Rugg said.

ParElastic’s existing investors — Point Judith Capital,  CommonAngels and LaunchCapital — also participated in the Series A round, which brings the company’s total venture capital to $8.7 million.

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The database in question is MemSQL, the eponymous offering from a startup company by former Facebook employees Eric Frenkiel and Nikita Shamgunov. The company, which launched in June, speeds up database operations by using in-memory storage and its own unique technique for converting SQL into C++, similar to what Facebook does for its PHP code. Frenkiel told me that other big-name customers already using the product include JPMorgan Chase, Hitachi and NY Life.

As of early January, Dan McCaffrey, GM of platform and analytics engineering at Zynga, told me that MemSQL was already storing about 70 billion rows of game data — from the server and database logs right up to social interactions. Right now, the biggest use of the MemSQL system is analyzing data from servers and databases about an application is performing. Compared with the company’s previous MySQL setup, McCaffrey said, “we can detect problems quickly and react to them much more quickly.”

Is a more personal Mafia Wars coming?

However, the deployment is just a few months old, and McCaffrey’s team has bigger plans for its new database. Among them is the ability to make decisions based on user behavior in real-time, rather than having to rely on pre-computed user segmentation and sampled datasets. That would mean applications could offer more-personalized decisions around in-game purchases or other recommendations, while Zynga’s burgeoning ad network could serve more-targeted and more-timely ads.

Both of these uses are important. Ninety-five percent of Zynga’s revenue currently comes from in-game purchases, although McCaffrey said it expects ad revenue to make up the lion’s share by 2015. Presently, Zynga pre-computes its user classifications nightly using its Vertica analytics system. If analysts want to query streaming data in real time, they can only do so against a sampled dataset that’s small enough to fit in memory.

With nearly 100 MemSQL nodes deployed already, Zynga can now store weeks worth of game data in memory versus merely days worth in its previous MySQL-plus-Membase setup.

In addition to improving the analytic process, the new database could help inspire entirely new types of games. McCaffrey noted that Zynga doesn’t have many games in which players interact simultaneously (most rely on players taking turns), nor does it have many multiplayer games. And although McCaffrey didn’t address the issue, one has to imagine Zynga’s expected foray into online gambling will also benefit from having a bigger, faster database to manage those real-time — and real-money — transactions.

One of the goals in the engineering group, he said, is “trying to introduce things that also get our game designers to think differently.”

Of course, a database alone isn’t going to make Zynga profitable and because MemSQL is commercially available, it’s hardly a trade secret. And as McCaffrey noted, although the experience has been good this far, MemSQL is still a small company and there’s a lot of work to do if it’s going to expand its presence throughout Zynga. But Zynga’s excitement about around a new database — and, in theory, it could have chosen any one of a number of new options — at least illustrates how critical the right technologies can be when trying to run a big business at web scale.

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ScaleArc, for its part, wants to let customers keep their MySQL, Oracle and SQL Server databases by making them faster and more intelligent. Its product, called iDB, sits between an application and its database and does a whole lot of good things — load-balancing, caching, SQL analytics and real-time dashboards among them. Recognizing the validity of certain new approaches for serving often-accessed data in a hurry (e.g., memcached) iDB’s cache actually uses a NoSQL database, although it’s backed up by the product’s standard security and high-availability features.

But for a company like ScaleArc, as well as the database products it aims to improve, the biggest threat probably isn’t NoSQL at all. Rather, they’re facing a new breed of SQL products — the so-called NewSQL movement — that promise everything developers and companies love about SQL with the scalability and speed that NoSQL can deliver. Among these offerings are Drawn to Scale’s HBase-based Spire, the SQL-into-C++ MemSQL and OLTP engine NuoDB, although there are many more.

Still, it seems clearer now than at any point in the past few years that SQL truly is not going anywhere, despite the early hype from the NoSQL camp. The most-important question that SQL shops might have to ask themselves now is not whether to stick with the technology they know and (maybe) love, but which flavor to go with to suit their particular needs around scale and performance. Thanks to technologies like ScaleArc, they might not have to swap their database at all.

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Click map to enlarge.

For comparison, check out Aslett’s next-most-recent database subway map, published in November 2012.

Click map to enlarge.

Note that the updated chart includes such shiny new entries as Akiban, NuoDB, and Parelastic. Kudos to Aslett for sussing this all out. I, for one, plan to print this out as a handy visual aid.

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NuoDB said it got a patent for its “elastically scalable database” from the U.S. Patent and Trademark Office in 15 months — it was filed March 8, 2011 and approved July 17, 2012. That compares with the average patent approval period of 34 months.

NuoDB co-founder and CTO Jim Starkey

“When I started what became NuoDB, the time for variations on existing themes was past,” NuoDB CTO and co-founder Jim Starkey  said in a statement.  ”If databases were to scale, a whole new approach was required, one unsaddled by ancient assumptions.The NuoDB patent represents a clean sheet re-invention of the relational database.  The interface is standard, but the underpinnings are so new that there weren’t even terms for its concepts.  The patent sailed through the patent office with a finding of ‘no prior art.’”

Update: The patent filing is here. According to the abstract, the patent application applies to:

A multi-user, elastic, on-demand, distributed relational database management system. The database is fragmented into distributed objects called atoms. Any change to a copy of an atom at one location is replicated to all other locations containing a copy of that atom. Transactional managers operate to satisfy the properties of atomicity, consistency, isolation and durability.

A patent gives its holder the right to exclude others from using the invention for 20 years from the application date  so in this case NuoDB is protected through 2031.

Starkey is a celebrity in database circles. He was the brains behind Digital Equipment Corp.’s RdB database (now part of Oracle) and Interbase (acquired by Borland) and is responsible for many of the breakthroughs in object databases. His company Netrastructure was acquired by MySQL, the popular open-source database, that is now also owned by Oracle.

His starpower is one reason NuoDB has gotten the attention of database aficionados, attracting backers including Mitchell Kertzman, general partner with Hummer Winblad who was former CEO of Sybase. Kertzman said he’d sworn off databases for the past decade because he found the technology stagnant and uninteresting. NuoDB changed his mind about that. The company more recently snagged Gary Morgenthaler as an investor and board member. Morgethaler was co-founder of Ingres, an early relational database power. He also co-founded Illustra with database superstar Michael Stonebraker, who is now with VoltDB. Those names give NuoDB even more heft.

As Morris explained to me earlier this year, NuoDB is often lumped in with NewSQL databases, which he finds to be an oversimplification. ”SQL is just one personality for us. We can be NoSQL or SQL, the innovation we have is much deeper,” Morris said. He prefers to compare NuoDB to BitTorrent in the way it divvies up tasks to any number of processors — avoiding bottlenecks — but somehow managing to keep all that data organized, accessible and safe.

We all know technology patents are tricky business — see GigaOM’s Jeff John Roberts’ continuing coverage of the raging patent troll epidemic  — but it does show that NuoDB may be onto something here with its self-scaling elastic database.

Time will tell.

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Akiban Server is a version of the company’s NewSQL database technology that can run independently. To date, Akiban beta testers have run Akiban Enterprise as an adjunct to existing SQL databases, usually, MySQL, using it to offload and speed up complex queries that can bog down performance. A developer preview of this standalone technology is downloadable now. Akiban is also making its Persistit B+Tree technology available under an open license. 

Akiban, like NewSQL pioneer VoltDB , maintains that NoSQL databases may be fine for some jobs but they also lack the sometimes-very-important niceties of SQL. They don’t handle queries very well and that’s a big problem for operational systems on which most companies run their businesses, said Akiban CTO Ori Herrnstadt.

Akiban’s key strength is its table grouping technology. “Table groups co-locate and store data together in a table group that is an object but is also fully ANSI-compliant relational architecture. As a result, we solve a big problem in that you can perform SQL [operations] more efficiently because you eliminate the cost of data joins,” said Akiban co-founder and CEO David McFarlane. (There’s more on this technology here.)

Developers can then work with that data directly as a JSON or XML object or can read it out as a JSON formatted document.

The company may be small — but it has big ambitions.

“Our opportunity is to be the leader in that operational database market which is SQL and transactional in nature. Hadoop can’t really play there — you need real-time results. Mongo doesn’t play there because it lacks transactional consistency and SQL support,” he added.

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Abadi and ThomsonThe researchers aren’t dismissing either NoSQL or NewSQL, but rather attempting to address the type of use case on which the popular TPC-C database peformance benchmark is based. That benchmark, which simulates an online retail application, requires ACID compliance — which NoSQL options can’t meet — and the ability to update records across database shards in the same transaction — something the authors claim NewSQL databases can’t do.

Why not just stick with Oracle Database and IBM DB2? Cost, especially at scale. As Abadi and Thomson point out in the blog, an Oracle system capable of handling 500,000 transactions per second costs $30 million in hardware and software expenditures.

So, what is Calvin? In a nutshell, it’s software that sits above above a scale-out storage system and turns it into a transaction-processing system by capturing, scheduling and executing transactions. Here’s how Abadi and Thomson describe it in the blog post, allthough the paper goes into much more detail.

Calvin requires all transactions to be executed fully server-side and sacrifices the freedom to non-deterministically abort or reorder transactions on-the-fly during execution. In return, Calvin gets scalability, ACID-compliance, and extremely low-overhead multi-shard transactions over a shared-nothing architecture. In other words, Calvin is designed to handle high-volume OLTP throughput on sharded databases on cheap, commodity hardware stored locally or in the cloud. … Calvin allows user transaction code to access the data layer freely, using any data access language or interface supported by the underlying storage engine (so long as Calvin can observe which records user transactions access).

Calvin, the researchers claim, can match Oracle’s 500,000 transaction-per-second performance running on commodity servers on Amazon EC2. The cost of the resources to run their benchmark was only $300. (Although, obviously, that doesn’t account for the cost of running the system continuously for years, potentially. Commodity physical hardware might be a better bet in the long term.)

Ultimately, Abadi and Thomson the researchers conclude, for transactions that can execute entirely on the server side, Calvin could be the foundation for an end to the current OLTP regime. The world certainly is hungry for something that can do what Oracle and IBM can do, but that costs what NoSQL databases cost (i.e., nothing, often). And Abadi has some distributed database street cred — the HadoopDB project he led is the foundation of Hadapt’s Hadoop-and-data-warehouse hybrid — so, especially if it’s open sourced, one can’t dismiss Calvin out of hand.

Feature image courtesy of Shutterstock user Semisatch.

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