Just as no year is complete for me without a viewing of Blazing Saddles, no Red Hat Summit is complete without a talk with someone from MongoDB.

We therefore posed a few questions for Paul Cross, Vice President of Solutions Architecture at MongoDB, and here’s what he had to say.

Roger: Tell us about the latest at MongoDB. Growth? Company direction?
Paul: A lot has happened at MongoDB in the past few months. Just after passing 1,000 subscribers and over 500 customers of our fully managed backup service, we announced MongoDB 2.6, our biggest release ever.
It includes major updates to our management application, MMS, including continuous incremental backup, point-in-time recovery, and automation. We are especially excited about the automation capabilities — users will be able to create MongoDB systems of any size and topology, with a single button click. They’ll also be able to manage their systems, including scale out, and hot upgrades with no downtime to their apps.
This is consistent with a major focus for us now – make MongoDB as easy to operate at massive scale as it is to build applications.
We have also added advanced security to MongoDB, putting it ahead of all other NoSQL products, in our opinion, and more importantly making MongoDB supported for critical apps in banks, healthcare organizations, federal agencies and other industries that require strict security.
Roger: How are you doing with developers?
Paul: Developers love MongoDB. We are now well past 7 million downloads of the database — and MMS is incredibly popular in the community, with over 35,000 users. We think the new enhancements to MMS and MongoDB will be well received in the community because they allow users to focus on what differentiates their business from their competitors.
Roger: And customers?
Paul: Tens of thousands of organizations use MongoDB, including 30 Fortune 100 companies. Significant customers include Cisco, eBay, MetLife and Forbes, and just this week Silver Spring​ Networks announced they are using MongoDB to scale its real-time Grid Data Platform. We are constantly announcing new customers; more recent announcements are available here and information on our customers can be found here.
Roger: You have an event coming up soon as well…
Paul: MongoDB will be holding MongoDB World this June, which will feature more than 80 in-depth sessions, including speakers from Bouygues Telecom, Citigroup, Expedia, Genentech, LinkedIn and Sanofi-Aventis. Amazon CTO Werner Vogels and Cloudera Co-Founder and Chief Strategy Officer Mike Olson will also deliver keynote addresses.  
Roger: I have a theory that all the world is hybrid cloud, or will be soon. How strongly do you agree/disagree with this?
Paul: From day one, MongoDB was designed for the cloud and will run optimally on any cloud deployments, with commodity hardware leveraged en masse to deliver scalability and availability beyond what is possible with monolithic, proprietary hardware.
Our customers need the flexibility to deploy in whatever environment is most advantageous, including costs, features, reliability, and their legal obligations. The bottom line is that flexibility wins. I’m excited to be at a company that embraces these challenges and provides options to our customers rather than a one-size-fits-all approach. 
Roger: How key is the role of Big Data in developing your solutions?
Paul: Everyone’s definition of Big Data is different. Our founders started MongoDB – the name comes from “humongous” – because at a previous company they spent far too much time building out infrastructures to manage their data. 
Recognizing early on that the mass amounts of volume of data being generated would become some of technology’s greatest pain points, they built a database that would eliminate the traditional friction points inherent in 30-year-old databases that weren’t designed for the challenges posed by modern application development.
In short, they built a database that would eliminate massive overhead, making it easy for users to deliver value to the world – simple to operate, fast development, open source, leveraging cloud architecture, and scaling to any size.
The result, five years later, is the fifth most popular database in the world, having quickly moved past other systems that have been on the market for decades. There is clearly something revolutionary about MongoDB, and it has a lot to do with the challenges Big Data poses in modern application development.

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Every company worries about competition. When I ran a large enterprise solutions organization, I took steps every day to ensure we were outpacing the competition. Frequently this involved making “build” vs “buy” decisions for the various product parts or services we needed to drive our business. In each discussion, I would ask my staff: “What is going to help us move faster or be more efficient? What will help us beat our competition?”
In today’s business world, IT is a significant driver of competitive advantage and the same considerations of “build” vs “buy” apply to IT, just as they do to other parts of the business.
Imagine the following exchange between a Line of Business executive and CIO of a company:

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As recent events have confirmed once again, no single company, organization or government is up to the task of securing the Internet. The never-ending cat and mouse game of exploits chasing vulnerabilities continues. The stunning Heartbleed discovery has shaken the online security establishment to the core. Claims of security and privacy for many Web servers were patently false.
We all know a chain is only as strong as its weakest link and the unintended back door information leak that is Heartbleed has undoubtedly allowed countless secrets to escape from secure servers, albeit as random pieces of a puzzle to be reassembled by the hacker. It will undoubtedly go down in history as the most widespread compromise of online services since the advent of the Web. Why? Because we now conduct an unprecedented number of so-called “secure” communications over SSL in every facet of commerce, government and the social web.

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loud providers Google, AWS and Microsoft are doing some spring-cleaning – out with the old, in with the new – when it comes to pricing services.
With the latest cuts, here’s a news flash:
There’s a new business model driving cloud that is every bit as exponential in growth — with order of magnitude improvements to pricing — as Moore’s Law has been to computing. Let’s call it “Bezos’ Law,” and go straight to the math

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MapDB is an Apache-licensed open source database specifically designed for Java developers. The library uses the standard Java Collections API, making it totally natural for Java developers to use and adopt, while scaling database size from GBs to TBs. MapDB is very fast and supports an agile approach to data, allowing developers to construct flexible schemas to exactly match application needs and tune performance, durability and caching for specific requirements.

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In this report Enterprise Management Associates (EMA) analysts explore the ways in which gaining visibility and control over high-privilege access helps organizations achieve regulatory compliance, assure responsible governance, and improve security all while reducing IT operational costs. The characteristics of an effective privileged access management solution are examined, along with evidence from EMA research that supports the values of a more consistent approach to operational IT control.

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No discussion of the Red Hat Summit 2014 would be complete without some discussion of Apache Hadoop. The happy elephant has now been pushing data for close to a decade, its distributed file system (HDFS) setting the tone for support of modern-day, highly distributed and very large databases in the cloud.

So I was pleased to have Robert Hodges, CEO of Hadoop-focused Continuent Tungsten, answer a few questions about his company’s world.

Roger: What’s the scope of the challenge you face in addressing big Hadoop deployments?

Robert: Hadoop is really very powerful as the way to concentrate and analyze information, so the key issue is how the information from existing transactional data stores gets added to Hadoop without implying additional load, application changes, or repetitive dump processes.

From our existing customer deployments, we know that the biggest challenge is getting the information into Hadoop as quickly and timely as possible from multiple different hosts simultaneously. Our customers often have many more transactional hosts running MySQL than they have Hadoop hosts, just because the scale-out and sharding required to support their transactional needs is so high.

Roger: What are the key pain points?

Robert: The key pain points are therefore the extraction of data from the transactional stores without implying additional load on these servers which are running their live customer facing website, while simultaneously loading large quantities of data that needs to be merged and analysed on the Hadoop side.

The replication solution based on Tungsten Replicator provides this very simply by placing a very low-level of load required for extraction of data, while continually streaming the changes over into Hadoop. Because this can be done on a server or cluster basis, it is easy to scale up the replication of data into Hadoop by adding more streams of replication data.

Roger: How critical is the real-time aspect of modern IT? How quickly is it growing?

Robert: It’s growing very quickly, and in some cases quicker than some company IT departments and the technology they support are able to cope. Replication has for a long time been the solution for this scale-out process, but the flows of this replication data are changing.

One of the key drivers behind the adoption of Hadoop and Cassandra and similar databases is the ability to parallel process the data to get numbers in real-time. You can see this in a wide range of different markets, from banking, through to social networking and online stores.

As we get access to more information, the services supporting them need to support that an ever faster rate. We all want the lowest rate on my plane ticket purchase, while receiving the absolute best benefits and service, and all those different elements rely on real-time analysis.

Roger: What does IT think of this?

Robert: Of course, this also presents a completely different problem for the IT departments. They must deal with how to get the data into a system so that it can be analyzed quickly. The location for your active transactional dataset is not the same as your analysis tools, and may be based on completely different quantities of raw data.

Transactional databases might be conveniently sharded into 50 or 100 different RDBMS of 100GB each, but analysis needs to process all 10,000GB of data collectively to get meaningful information. That means that the IT infrastructure needs an effective way to combine and transfer this active data.

It’s also clear from recent advancements in querying and processing techniques built on top of Hadoop that Hadoop itself is moving into a more real-time tool. Spark, Storm and other query engines provide very fast query and analysis on very large datasets, taking advantage of the distributed nature of Hadoop, and the increasing RAM and CPU power in evolutions of new hardware. Compatibility with Spark and similar live query mechanisms in Hadoop will form a key part of the next evolution of all Hadoop deployments.

3. How key is the role of Big Data in developing your solutions? How important is the term Big Data to you?

Big Data has been a significant requirement for our customers and their needs for some time, but we have definitely seen a shift recently from the scale-out, sharded nature of the typical RDBMS towards concentrating that information for analysis in Big Data stores. As that movement of data moves into the real-time it will be critical to the tools we develop to help make the transfer and management of data replication as easy as possible for our customers.

To us as the provider of the tools that enable our customers to easily share and transfer data, Big Data is therefore as important to us as it is to our customers. Of course, transactional databases are not going away, and we certainly don’t expect that to change, but Hadoop and other Big Data solutions are being brought to work alongside these active data stores. Continuent will certainly be looking to expand our different solutions and techniques to bridge the gap between RDBMS and Big Data.

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Continuing a series of brief interviews with some of the technology execs at this year’s Red Hat Summit in San Francisco, we turn our attention now to Sandro Mazziotta, Senior Director of Product Management, eNovance.

This company is based in Paris with a North American office in Montreal, is an OpenStack company, and focuses on private and hybrid clouds as well as multi-cloud management.

Roger: How has your business grown in Europe? Who are your key customers? How important will North America now be?

Sandro: We started as a managed services app provider, shifted to becoming an IaaS provider, then moved to becoming a services and solutions provider focussing on OpenStack and open source in general.

We started by doing business in France and then in EMEA. Cloudwatt is a major customer for us, for example, and we continue to focus on EMEA and while expanding to the North American market.

There is a clear trend in adoption of OpenStack happening world wide. We are seeing a lot of traction for large-scale OpenStack deployments. North America remains the birth place of cloud computing, and will continue to be a high-growth market as new technologies like OpenStack continue to mature.

Roger: How critical is the real-time aspect of modern IT? How quickly is it growing?

With the emergence of mobile applications, companies are generating more and more information to store and retrieve in the cloud. This creates a fast-moving and growing market opportunity for more modernized IT infrastructures based on OpenStack. The challenge however is for mobile applications to access the right data in real time.

Roger: How key is the role of Big Data in developing your solutions? How important is the term Big Data to you?

We focus on large scale implementation of OpenStack. For Big Data storage, OpenStack is the only open-source cloud management stack to deploy Big Data applications in the cloud – it’s the preferred way to store data. This is particularly important for us with our focus on large-scale deployments.

Clearly, I just scratched the surface here, so expect to follow up with Sandro to glean some more insight from companies like this that are attacking very large challenges within the realms of the cloud, Big Data, and presumably the IoT.

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