Apparently no one, not even those who are building complex web applications. And new startup Orchestrate.io just took a massive $3 million seed round to prove it. Orchestrate takes the queries that developers would typically write in order to build an application, such as geolocation, time-series, social graph, full-text search, and more, and unifies everything a developer would need in a single API.

In other words, all the time and resources that would typically go towards designing your data solution can now be redirected to building your application, as Orchestrate outsources the need for you to own and manage your own databases.

“Complex apps require highly optimized queries, so much so that major companies such as Facebook and Google wrote custom big data databases like BigTable to manage them,” founder and CEO Antony Falco told me yesterday. “Typically you would devote 20-25 percent of your resources to data management, so there’s lots of savings. But when creating new apps, you can also reduce the time barrier to building services, getting multiple weeks of savings.”

Antony Falco, CEO and founder

One of those savings: Often companies have had to run or access multiple databases to enable their applications. All of them have to be monitored and maintained, scaled as your app grows, and distributed geographically and across multiple service providers to ensure high availability and low latency.

With Orchestrate, that’s all built in, Falco told me, including geographical distribution. Simply use the Orchestrate API to insert, read, and update data, and pay no attention to whatever is happening behind the curtain.

Falco used to be a VP at Akamai, the content delivery network, so he knows a few things about scalability and access. And talking about scalability, Orchestrate is looking to fill a pretty big niche.

“Database and operating system licensing, servers, storage, power, labor, outsourcing, and professional services represents a market that exceeds $100B annually,” Falco said in a statement. “We believe our service will save our customers significant time and money, allowing them to instead focus on what matters most — the end-user.  With Orchestrate.io, our customers can build better apps, faster.”

The $3 million is for getting Orchestrate’s existing solution into production and hiring more engineers.

It’s a largish seed round — you typically see $750,000, $500,000, or less for seed rounds, but Falco, who acknowledged that it had some aspects of an A round, says that it will help the company expand further. And, for a company with global aspirations, some expensive requirements are just table stakes.

“With $3 million we will be globally distributed,” he says.

Falco is a serial entrepreneur, also founding Basho Technologies, maker of open-source distributed database Riak. Orchestrate was founded just three months ago, in March 2013, and is based in Portland, Oregon.

The investment was led by True Ventures with Frontline Ventures and Resonant Venture Partners joining in.

photo credit: adesigna via photopin cc

July 9-10, 2013
San Francisco, CA

Tickets On Sale Now

HG Data uses a data-driven approach to help salespeople build lists of potential enterprise customers, and is ready to disrupt the legacy IT market.

The Santa Barbara-based startup today closed a $2 million funding round led by EPIC Ventures.

“While LinkedIn maps the connections between people in business, HG Data maps the connections between businesses themselves – who sells to whom, who buys what, and who partners with whom,” said Craig Harris, CEO and founder of HG Data in a statement.

The company has been building out its algorithms for the past two years. More specifically, it uses machine learning technology to updates its databases with information that is publicly available from press releases, white papers and the like. One of HG Data’s customers might use the tool to pinpoint a company that still runs on a specific type of legacy hardware, and pitch them an alternative.

The company claims its customers can use the data to bolster lead generation, market share analysis and marketing automation.

Angel investors in the round include Kevin O’Connor, founder of DoubleClick and current CEO of FindTheBest; Eric Kanowsky and AJ Rice, both co-founders of Software.com; and Tim Baskerville, former CEO of JupiterResearch.

Sept. 9 - 10, 2013 San Francisco, CA

Early Bird Tickets on Sale

Cloud-computing giant Rackspace has made a small but smart acquisition in ObjectRocket, a MongoDB database service.

Rackspace senior vice president of corporate development Pat Matthews said, “Customers have been asking for a powerful database,” and the acquisition is in line with their open cloud strategy. MongoDB was the best option from Rackspace’s perspective as it’s one of the fastest growing NoSQL open source databases, and many existing customers already use it.

According to a report from British technology research firm The 451 Group, NoSQL software revenue is expected to grow at an annual of 82 percent to reach £141 million ($214 million) by 2015.

Database technology floods the market, but Matthews said that MongoDB has experienced a “runaway success” with developers. It’s easy to get started and supports about a dozen programming language on the Web, including C, C++, C#, JavaScript, Node.js, and Scala. But it can be difficult to manage and scale, which is where ObjectRocket comes in.

In the future, Rackspace is likely to support other database technologies.

ObjectRocket co-founder Kenny Gorman has been recognized as a “MongoDB Master,” an award 10gen gives to only 35 MongoDB contributors around the world. (Check out a video interview with Gorman and Rackspace’s chief developer evangelist Robert Scoble below.)

The full team will relocate to Rackspace’s San Antonio headquarters (they previously worked remotely), and customers should see the benefits of an integration in a matter of weeks.

On the topic of Rackspace’s broader acquisition strategy, Matthews revealed that his team doesn’t plan to buy established companies. “We have a good sales and marketing engine and know how to acquire customers,” he said. Instead, they are on the lookout for small, under-the-radar teams with impressive technology. The company’s other recent acquisition, MailGun, was a six-person operation with just a seed round of funding.

Rackspace has not disclosed the terms of the deal.

ScaleArc has pulled in $12.3 million for its second funding round to bolster its efforts to make SQL databases easier to manage.

The Silicon Valley-based company simplifies the way you deploy database environments. It claims its ScaleArc iDB software can lower costs by up to 50 percent for its customers, which include online gaming company Kixeye and Weather Decision Technologies.

Most valuable data is stored in SQL, but caching data is typically a manual task that required a team of engineers. ScaleArc automates this complex process to give its customers a visibility into every query, provide real-time analytics and instant troubleshooting, and more.

TechCrunch’s Alex Williams predicts that the company will likely use the infusion of capital to attack the NoSQL market. This will ensure that the company can stay ahead of its competition, which includes Citrix and Netscaler.

To further the development of its database infrastructure software, ScaleArc raised funding from Accel Partners with participation from Trinity Ventures and Nexus Ventures. This brings the company’s total investment to $18.3 million.

With all this talk of disruption in the enterprise, young founders should not underestimate legacy vendors. Business software behemoths like SAP and Oracle have their eye on the big trends, whether it’s cloud, “big data” or mobile computing, and are finding ways to filter out the most innovative technologies from the noise.

At CloudBeat, VentureBeat’s recent customer-focused cloud conference, I caught up with Sanjay Poonen, president and corporate officer at SAP, who specializes in technology and product innovation. That afternoon, Poonen was joined on stage by one of the company’s biggest healthcare customers McKesson to discuss ongoing concerns about the cloud and their reasons for selecting SAP.

In this ensuing discussion, Poonen revealed that SAP has hedged its bets on its own big data solution, known as HANA. He told me that IT will be “transformed” by big data. In 2013, he said, “a lot of the hype goes out [the door] and the substance starts to show up.”

Watch the video for more of SAP’s predictions on the big tech trends for the coming year.

SAP (Source) from VentureBeat on Vimeo.

When we consider the “big data” trend, it’s most often in terms of how large corporations like Macy’s and Starbucks will use vast volumes of consumer data to grow their business.

But how about the little guy — the coffee shop on Main Street that is struggling to compete with Starbucks to keep its doors open?

Intuit, the maker of financial management products for small businesses, currently has hundreds of engineers tasked with bringing the benefits of big data to Main Street. The company envisions a future where small businesses will be armed with data to help them make strategic business decisions and drive consumer sales. It’s turning its database of small business finances into tools to help its customers save time and money.

Small businesses have a “treasure trove of data”

Michael J. Radwin, Intuit’s director of engineering

In an intimate meeting at the company’s San Francisco office, CEO Brad Smith told reporters that Intuit is stressing three things: privacy, innovation, and the accessibility of data. For Smith, that big data can be used to benefit the little guy by 2020 is a no brainer, given the sheer quantity of relevant data in Intuit’s grasp. (Over the next decade, Emergent Research posits that it will increase more than 40-fold.) With its 60 million global customers, Intuit is currently sitting on a “treasure trove of data,” in Smith’s opinion. He is fond of saying that 20 percent of U.S. GDP flows through Quickbooks, Intuit’s small business accounting software.

One of the most prominent examples is Intuit’s Small Business Index, which pulls together sales, profit and employment data from a statistical sample of 70,000 small businesses (with fewer than 20 employees) that use Quickbooks and its online payroll software. Small business owners can use this data to determine when it’s the right time to cut back on expenses or hire some additional help. This effort was spearheaded by Nora Denzel, senior vice president of Big Data, Social Design and Marketing, with her 100 person-strong team of researchers. Note: Denzel has subsequently left the company.

However, consumers are concerned that their personal information is being used by businesses for targeted advertising.

Surrounded by members of the media, Smith is well-prepared to deflect criticism on the topic of consumer protections and privacy — chief privacy officer Barb Lawler sits front and center. Smith frequently repeats the company mantra, ”Our view is that this is not our data, this is our customer’s data.” He said the company has been working with “every agency there is” to ensure that your data will be secure, and that it won’t be used without permission.

“We can improve your life with your permission”

Intuit CEO Brad Smith

Smith hopes that most consumers and small business owners will voluntarily give up their data — “[we] can improve your life with your permission,” he stresses.

One of his favorite examples is how employees noted that two-thirds of Intuit’s customers using the Quickbooks product, a small business accounting software, were recently denied a loan.

“Banks were afraid to take the risk and we are sitting in the middle of the Quickbooks data [and] can qualify that individual,” Smith explained. The company analyzed whether applicants were paying their bills on time, and the banks were notified about those that were least likely to default on a loan. Smith claims that $10 million in loans were subsequently provided to Intuit’s customers.

I asked whether the company will consider social data  – the number of “likes” on a brand’s Facebook page — as an indication of an individual’s ability to repay a loan on time. Social finance startups like LendUp are beginning to use this information to get a better picture of the borrower. Smith said the viability of leveraging data from social networking sites is “yet to be determined.”

With 8,000 employees, can Intuit spearhead innovation?

Inspired by Google, Intuit’s next-door neighbor at its Mountain View, Calif. headquarters, it has been company policy for years to let engineers devote 10 percent of their time to innovative projects. According to Smith, this yielded Intuit $100 million in revenue in 2011.

The top execs are keen advocates of Eric Ries’s ”Lean Startup” method — the company recently invited the author and serial entrepreneur in to its offices to help them internalize a culture of experimentation, and rapid product cycles. Ries worked with the company’s most talented engineers, tasked with developing new technologies to arm small businesses.

One of the top engineers is Michael J. Radwin (pictured above), a data nerd who has introduced text analytics, recommendation services, and data-driven algorithms in his two-year tenure at Intuit.

Shortly after the meeting, Radwin pulls me aside to demo one of the projects he’s most proud of — a local business recommendations service intended to provide more detail than Yelp. The idea was conceived by an engineer, and a team formed to bring it to fruition. It’s in beta, and is primarily used today to give Intuit employees, analysts, and the press an idea of how data might be used in the future.

Radwin views Yelp data as highly deceptive, and skewed to favor large franchises with digitally-savvy customers. By integrating information from a variety of external sources including Mint.com (the personal finance company Intuit acquired a few years ago), his team created a detailed map of businesses in any area. Customers can perform a simple search to uncover the hair salons or coffee shops with the highest customer retention rates and most competitive prices — more often than not, its the family-owned businesses that emerge on top.

If Radwin has his way, this prototype will likely be under development in the coming years. It’s just one example of how data can inform consumers, and be used a weapon for the little guy on Main Street.

Kids back-to-back image via GELPI, Shutterstock

Most experts agree that a traditional database can’t support the rapidly accelerating mess of unstructured and structured data contained within the enterprise. However, where this consensus falls apart, is on the right approach to tackling the “big data” problem.

In the ongoing battle between the NoSQL and SQL databases, Splice Machine is one of the few young companies that has come down firmly on the side of the latter. Today, the San Francisco startup has raised $4 million in first round funding for its SQL database build on top of the open-source Hadoop Distributed File System.

According to its founders, popular NoSQL databases like HBase and Cassandra Hadoop, can handle large volumes of data that do not fit neatly into structured tables, rows and columns. However, they are not equipped to support the full spectrum of business intelligence (BI) products.

If their solution works, it’s every enterprise investor’s dream. Customers will receive all the benefits of NoSQL (flexible schema for unstructured data, scalability), as well as a close integration with their SQL BI tools and favorite data visualization services like Tableau.

“The NoSQL community threw out the baby with the bath water. They got it right with flexible schemas and distributed, auto-sharded architectures, but it was a mistake to discard SQL,” said Monte Zweben, the company’s CEO in a statement.

With experience at both Oracle and Nasa, Zweben may have the right background for a big data founder. He worked at the NASA Ames Research Center as the Deputy Branch Chief of the Artificial Intelligence Branch, where he dedicated his efforts to the Space Shuttle program. He went on to co-founder Blue Martini Software (which experienced a successful IPO in 2000); prior to that, he was a vice president and general manager at PeopleSoft, acquired by Oracle in 2005.

The company’s closest competitor is Drawn to Scale, a Berkeley-based startup with a SQL database for Hadoop. It  has just shy of $1 million in venture funding in the bank.

Splice Machine’s first funding round was led by Silicon Valley firm, Mohr Davidow Ventures.

BriefMine, a startup launching today, wants to make access to legal research more cost-effective. It is one of only a handful of legal tech companies using technology to push the boundaries of legal practice.

As we reported, it takes guts to tackle the legal tech space. The challenges include old-fashioned regulations and constant push back from the target market. And yet, notoriously underfunded, it’s a huge market opportunity that has been untapped by Silicon Valley’s venture capital firms and angel investors.

Burdened by decades-old technology, the legal industry is ripe for disruption. One of the recent shifts that has taken place in the legal industry is that most lawyers don’t work at stuffy, corporate practices. Today, roughly three-quarters of 1.2 million lawyers in the United States work at small firms. These lawyers struggle to afford costly legal research tools like Lexus Nexus and WestLaw.

For legal tech entrepreneurs, this is an opportunity for a simpler, cheaper alternative. “It has historically proven a tough nut to crack,” BriefMine’s founder, Harry Zeitlin, told me. “By creating a high technology platform at a very low price point, we are paving the way for further, and much-needed disruption, which will ultimately benefit legal providers,” he said. 

The company has developed a database filled with legal briefs and opinions. For lawyers, relevant information will surface using a simple query-based, natural-language search. Briefmine says the beta product is already being used by 100 lawyers at small firms, and advisors have jumped on board from firms like Wilson Sonsini Goodrich and Rosati, a favorite for tech companies. In the future, it may compete with TraceLaw, a San Francisco-based startup that is building a case law search engine. 

Harry Zeitlin, Founder of BriefMine

In future, BriefMine plans to make money by charging law firms for the service on a subscription basis and creating a section of the site where lawyers can advertise their own content and collaborate with other lawyers. 

BriefMine was founded in June 2012 and has grown to a team of five employees. Founders Zeitlin (pictured, left) and Gabe Lupin attended Stanford University together; lead engineer Jigar Gandhi is studying for his LSAT and plans to attend law school so has an established interest in the space.

According to BriefMine, the idea originated during a conversation with an attorney at a small law firm. “He [the attorney] mentioned that briefs would be invaluable to preparing his argument, but that the fees associated with these services were exorbitant,” said Zeitlin.

The San Francisco-based startup is a bootstrapped effort, and the founders are looking to raise their first round of funding.

Sept. 9 - 10, 2013 San Francisco, CA

Early Bird Tickets on Sale

Yesterday, Google Research pulled the shroud off Spanner, Google’s “scalable, multiversion, globally distributed, and synchronously replicated database,” claiming to have created “the first system to distribute data at global scale and support externally consistent distributed transactions.”

The only problem?

TransLattice has been deploying a globally available, geographically distributed multinode database for almost two years.

I wrote about TransLattice almost two months ago when the company finally went public. The company’s core product is “TED,” TransLattice Elastic Database, and it enables a live, functional, operational database with multiple nodes all over the world, without simply syncing, replicating, or cloning.

Spanner, which appears to be in use at Google, maintains global consistency with the assistance of atomic clocks and GPS. The database automatically places data closest to where it’s frequently needed, replicates elsewhere for redundancy and backup, and can scale impressively: up to “millions of machines across hundreds of datacenters and trillions of database rows.”

That sounds like greater scalability than TransLattice, which two months ago was running on up to 12 nodes and was working on capability for 20 or more nodes.

But TransLattice believes it was first, saying that Google’s system, while interesting, is much more a key-value store than a true relational database, which while enabling huge scale, would not work for enterprise applications.

In other words: It’s built for exactly what Google does every day.

In addition, however, TransLattice co-founder and chief technical officer Mike Lyle called Google’s claim to be first into question.

“Most dubious is Spanner’s claim to be the first system with these properties. TransLattice has been delivering to customers true SQL conformance and geographically distributed relational databases with all of the ACID guarantees for nearly two years.”

I talked to a Google representative about Spanner and TransLattice, and while she did not have a specific quote, she said that Spanner is a Google Research project, not a specific product.

Any specific claims in the paper are not claims Google per se is making, and while Spanner is deployed right now, she could not comment on how long it has been operational.

Reading through the Google Research paper (OK, skimming it) it appears that Spanner has been built for a different use-case than TED. And both, to be completely frank, are incredible achievements.

No matter which one happened to be first.

photo credit: IronRodArt – Royce Bair (NightScapes on Thursdays) via photo pin cc

Sept. 9 - 10, 2013 San Francisco, CA

Early Bird Tickets on Sale

Late last year, database and business management software company SAP had a blow-out quarter, the company’s best in 40 years. Double-digit growth and $2.1 billion in profit: not bad at all.

One of the causes, according to the New York Times, was the company’s quick adoption of in-memory processing. But what is in-memory processing, and how does it help?

You could think of it as kaizen for the data center.

Kaizen is a Japanese-inspired process of simplifying manufacturing by removing unnecessary steps and waste, like waiting time. One of the goals in a kaizen-ified factory is to bring all source materials and parts close to the place where they are actually used.

That’s exactly what in-memory computing does.

One of the main uses for in-memory computing is the real-time manipulation of huge data sets. Let’s consider an example: Home Depot’s sales. Executives at this company don’t need to know the location of every rake, nail, lawnmower, and 2×4 for a month, or even a year, but their databases do. When executives are attempting to understand how sales are doing, or trying to forecast future earnings, or even modelling how changes in business strategy might affect sales, logistics, and revenue, they’re working with big data. This data is kind of like the raw materials entering a factory. The closer those materials are to the factory, the more efficiently the factory can produce finished goods: In this case, business analytics.

In a traditional database, the data lives on hard disks similar to the drives in your desktop or traditional laptop. Those are slow and distant, arriving at the “factory,” the server’s CPU, via wired connections. And when gigabytes or exabytes of data are needed, one of the main slowdowns on database performance is data access. The raw materials just can’t get in fast enough.

In an in-memory database, the data lives right next to the CPU, not in the next town. And it doesn’t live in hard drives that need to actually physically spin (like a CD or old cassette drive) in order to allow data to be found and read, and then transmitted. Instead, the data lives in main memory — RAM — that is instantly accessible and, in some cases, on solid-state drives like those in USB thumb disks or a MacBook Air. That makes the data much faster and more accessible to the CPU, meaning the server can churn out analyses of those Home Depot sales figures that much faster.

Since the theoretical limit for memory in a 64-bit database system is 18 billion gigabytes, there is no lack of memory capacity. Also, there is no problem holding as much raw material — data — as the company wishes, right there in the “factory.”

Which means that reports and projections requiring the analysis of hundreds of gigabytes of data can be done in seconds, not hours. And that in turn makes enterprises both faster and smarter.

Image credit: Desiree Walstra/ShutterStock

July 9-10, 2013
San Francisco, CA

Tickets On Sale Now

Imagine a functional, live, operational database living on separate servers scattered around the globe in say, San Francisco, London, Dubai, Moscow, and Johannesburg, simultaneously. Not synced, replicated, or cloned — but a single database without a single location.

Now tie up your jaw.

Actually, no imagination is required, because today TransLattice announced the world’s first geographically distributed relational database. The company calls it TED, or the TransLattice Elastic Database.

“For the last 15 years, people have been trying to solve the distributed database problem,” TransLattice vice president Louise Funke told VentureBeat. “This is unique … it’s truly one database with data in multiple locations.”

It’s the perfect solution for companies that absolutely must remain live and functional — no matter what happens to electrical power generation in northern Virginia. More on that later.

The Santa Clara company’s goal was to create a database that can live in multiple locations simultaneously but does not require any one of them.

It’s the ultimate hydra, with many heads. Or, if you prefer, it is a database modeled after the internet itself, designed for ultimate survivability with multiple nodes, self-healing capacity, and no single vulnerable center.

How does Elastic Database work?

TransLattice, founded in 2007, only released its first product last summer — the first years were spent solely working on the math and building the technology. TED is built on a foundation of PostgresSQL, but as you would expect, the company has made major modifications to how the system maintains consistency.

“At a high level, we’re breaking up the data — sharding it — and breaking it up according to three things,” Funke told me last week.

Those three things determine where data lives in the database.

The first is policy — in some cases an enterprise cannot permit data to leave a particular country or region. The second is history — how often a particular set of data is accessed, and where it is accessed from. And the third is randomness — the data is never just confined to a single disk or node.

Data in TED is always on multiple nodes for both reliability and robustness as well as accessibility. But it is not on all nodes.

At its core, the Elastic Database relies on a set of algorithms called Global Consensus Protol, which commits thousands of transactions simultaneously and ensures that data is consistent and accurate throughout the entire set of locations (currently up to 12 nodes, and soon to be more).

“People have said you have to give up consistency in order to scale geographically, moving to solutions such as noSQL,” says Funke. “But we don’t give up consistency.”

In fact, Elastic Database is fully ACID-compliant, just as a traditional relationship database management system. (ACID is a model describing the properties of reliable database standing for atomicity, consistency, isolation, and durability.)

But what about latency?

The immediate concern with a geographically diverse database is, of course, latency: How big can the database get, how active can it be, and how many nodes can you have before the communication between nodes that is necessary to ensure consistency overwhelms the communication between application and data that the database is intended to serve.

Source: TransLattice

Part of a TransLattice database dashboard

In other words, when will internal communication destroy usefulness?

“No single node has a full copy of the data,” Funke says, “but we maintain copies of the data between the nodes.”

That helps on the one hand: Pre-positioning data when and where it’s most likely to be needed speeds database response. And it hurts on the other: When distributed data is updated in one location, it must be updated in all locations.

TransLattic says it has solved those issues.

“Our system is very unique — we monitor communications between nodes to understand bandwidth and usage,” Funke told me, “so that when we make data placement decisions, we place it where it’s being used. We can place it for optimal performance.”

Actual multi-continent installs … today

The announcement today is not just a product in principle. TransLattice has real revenues and real customers using the technology today, Funke says. Getting names and contact information is a challenge, however, because the types of customers using this are not very forthcoming — about anything.

Think three-letter agencies. Think people with big guns … and no, not the ones you get from doing curls.

“We have a lot of public-sector clients in the defense and intelligence industries,” Funke said.

The scenario she outlined for me is classic: Imagine you are the U.S. military. You need certain datasets as close to the battlefields as possible. So you plunk down a server in Afghanistan.

It needs to move from time to time, and maybe it gets blown up occasionally. But that doesn’t matter, because you can reconstitute local nodes easily.

New nodes from bare metal in 20 minutes

If that server in Afghanistan does, in fact, get blown up, local techs can resume operations incredibly quickly.

“Customers can very simply add new nodes to their clusters,” Funke says. “If one fails or you suddenly need to set up a temporary operation, you simply can take a node and plug it into your network.”

The other nodes will recognize it immediately, and within minutes, TED is populating it with data and users are accessing information from all across the database.

Source: TransLattice

TransLattice dashboard showing data location

“You can get a new node running in 20 minutes from bare metal, which is unheard of,” Funke told me.

Cloud yes, high costs no

Given that TransLattice’s database seems to run much like a geographically-distributed cloud, I wanted to know whether it can be run on other companies’ clouds.

TransLattice says it can.

TED can be run on virtual machines, it can be run on Amazon EC2, or it can be run on a TransLattice appliance. Or it can be run on all of them simultaneously.

“You can use whatever mix of hardware you want,” Funke says. “The nodes do need to be relatively similar in size and I/O capacity and compute capacity.”

And the costs, according to the company, are low — as much as 60-80 percent less than a comparable IBM DB2 solution or an Oracle RAC solution. Except of course that those do not come with the ability to run your database on both sides of the Atlantic at the same time.

Use cases

In addition to military and security customers, TransLattice is seeing considerable uptake in the financial sector.  Businesses are more geographically diverse today, Funke told me, and many are dealing with regulatory environments that do not allow the transfer of private user data out of country.

TransLattice enables that with protocols for where data can live.

In addition, however, many financial organizations have datasets that are too large to replicate, making it harder for the organization to give all parts of the company access. Instead they silo the data, limiting the company’s ability to effectively use the data for business intelligence and strategy.

Elastic Database, according to TransLattice, solves that problem as well.

The question will be, now that TransLattice is publicly available: Do the advantages of regionalization outweigh any of the advantages of tradition databases from Oracle, IBM, and others?

Image credit: Toria/ShutterStock

“I don’t really see it as a replacement for Oracle,” he said. “The only reason Oracle exists in-house is for companies that want on-premise databases.”

A large part of that probably has to do with security. Many companies are reluctant to ship their data off to remote cloud servers and databases because they think it will be compromised. A lot of companies also have strict security regulations that keep them from jumping on board the cloud because of compliance issues. Campos said Facebook still uses Oracle for its on-premise databases.

Salesforce has been championing the move to the cloud for some time now. The company’s CEO, Marc Benioff, even brought a customer that had a poor experience with Salesforce on stage during the keynote to try to convince him to move to cloud computing products like the company’s customer relationship management (CRM) software. The next logical step was to provide companies with a cloud-based database, which the company launched at Dreamforce 2010 this year. With the launch of database.com, it’s competing against some traditional powerhouse database providers.

But Campos applauded Salesforce on its move toward being more of a development platform. That means the company is providing developers “with a few of sharp tools” to produce a lot of web-based applications and services that range anywhere from asset management to customer relationship management (CRM) software. The company is trying to focus on being a catalyst for developers trying to make web-based applications. It’s a move that Salesforce has been focusing on with the acquisition of companies like Ruby on Rails development assistant Heroku.

July 9-10, 2013
San Francisco, CA

Tickets On Sale Now

Salesforce, one of the largest providers of web-based customer relationship management (CRM) software, announced today that it is launching a cloud-based database at Database.com for its developers.

Salesforce has recently begun a shift toward a more developer- and employee-centric focus that has drawn on lessons learned from the consumer market. That means opening up the software to make it easier for developers to create new applications for the service and giving them the computing firepower to handle it. Its flagship software, which is billed as a software-as-a-service, is run on cloud servers that can handle a lot of heavy lifting and is web-based. The next logical step was to provide developers with a spot in the cloud to quickly store and access data, said Ariel Kelma, vice president of platform product marketing for Salesforce.

“Instead of designing a database around the needs of a database administrator, we need to develop it around the needs of a developer,” he said. ”We expect the audience for database.com is more of a developer audience than the typical user.”

A big focus of Database.com is security — which is something that prevents a lot of companies from fully moving their data onto the cloud. Most companies are concerned that offloading sensitive information onto remote databases makes it more vulnerable. A lot of companies also have a number of compliance rules that keep them from doing so. To fight that perception, Salesforce is bringing in its 11 years of experience with security.

“Whenever there’s some new innovation in security or someone suggests an enhancement, it goes out to all of our 87,000 customers immediately,” Kelma said. “Users don’t have to wait however many months for it to trickle down.”

Database.com is available under the freemium model — the first 100,000 records and 50,000 transactions each month are available for online storage on Database.com for free. After that, it’s $10 each month for another 100,000 records and 150,000 transactions. For enterprise users, it’s $10 per user per month.

Salesforce’s micro-blogging service Chatter recently changed over to a freemium model — in which a stripped down version is available for free, and users can upgrade to the standard model. That came as a result of pressure from other new enterprise applications like Yammer that offered their services for free at first.

“We’re big fans of the freemium model,” Kelma said. “If you’re a multi-tenant cloud provider, it’s one of those things you just have to have.”

But it all boils down to a pretty common trend in the enterprise software industry. Lessons are being drawn from the consumer space, where giants like Facebook and Twitter are teaching traditional enterprise giants the new rules of software. Salesforce learned how powerful micr0-blogging can be from companies like Twitter and Yammer, and applied those rules to Chatter. It’s now learning that its customers have enormous amounts of data, and need some place to store it and quickly access it.

The cloud-based database is quick. Information that was changed via the web-based interface through Salesforce was changed in both command line and Facebook profiles that accessed the database within seconds in a demo of the product. So it will be interesting to see just what developers can do with the service.

July 9-10, 2013
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10gen, developer of the open-source software for databases called MongoDB, announced today that it has raised $6.5 million in its third round of funding from Sequoia Capital.

MongoDB is billed as a software set for managing large-scale databases for web sites. The software allows companies to manage their content and events, and also includes an analytics suite that tracks site usage.

Its users include a number of prominent startups like check-in service Foursquare and Bit.ly, which allows web surfers to shorten long links into more manageable lengths for micro-blogging.

The New York, N.Y.-based company launched MongoDB in 2007 and makes its money by providing commercial support for bigger businesses that employ the database software. It also manages the open-source community for the MongoDB software set that sees around 90,000 downloads each day.

Prior investors Flybridge Capital Partners and Union Square Ventures also participated in the most recent round of funding. That brings its total funding up to $11.4 million. Flybridge Capital Partners led an earlier round worth $3.4 million, and Union Square Ventures led 10gen’s first round with $1.5 million in funding.

Semantifi is one of 70 companies chosen by VentureBeat to launch at the DEMO Fall 2010 event taking place this week in Silicon Valley. After our selection, the companies pay a fee to present. Our coverage of them remains objective.

Google and other popular search engines only search about 1 percent of the Web, according to research data from UC Berkeley. That just isn’t enough for deep-Web crawler Semantifi, which launched its new search engine at DEMO Fall 2010.

Semantifi offers users a way to search for specific data through a search engine powered by user-created apps. One example: searching for U.S. population numbers separated into age and gender. It uses the “deep Web,” where information is stored in databases and is not immediately accessible through traditional search engines that just search the text and images of websites. The technology to power Semantifi has been in development for 5 years.

Wolfram Research’s Wolfram Alpha, as well as some other data-powered search engines, also provide “answers” for searches on the Internet, such as a mathematical problem or what the national bird of Sweden is, but Semantifi offers users a chance to power the search with their own sets of data.

The Stamford, Conn.-based company is currently run by a team of 30, and has raised $3.5 million in one fundraising round in September 2008 from Connecticut Innovations and Launch Capital, as well as some individual investors.