Couchbase's main product is its Engagement Database, which is built on NoSQL technology and designed for 'the massively interactive enterprise'. The company lists Tommy Hilfiger, Ryanair, United Airlines, Amadeus and Betfair among its customers. ZDNet spoke to Couchbase CEO Matt Cain to find out more.
ZDNet: When was the company formed?
Cain: Officially it was 2011 and it was the result of the merger of two separate companies -- one was an open source cache and the other was a document-oriented database. This was a very important foundation for the Couchbase data platform.
Since 2011, we've achieved significant growth and we now have more than 400 customers and cover 350 employees around the world.
Our mission is to be the data platform that revolutionises digital innovation and what we've built is the world's first Engagement Database. What that essentially means is that we're in the business of helping our customers drive their digital transformation initiatives.
And that transformation initiative is there to help them with web, mobile and IoT applications that touch their end customers. At the same time, it is a productivity application that they deploy internally so that, as companies, they can become more effective in all aspects of their business operations.
We're built on a powerful NoSQL engine which allows us to deliver scalability, performance and reliability to large enterprises in a unique and differentiated way.
You say it's a mission-critical application?
Sure, there are a couple of things that are core to our differentiation and let me talk about the essence of the Couchbase data platform. We have an in-memory/share-nothing/scale-out architecture that supports a flexible data schema via JSON. That's the core of the database engine that allows us to support applications with no latency and enables us to support the very large applications that exist in the enterprise.
What we have then done is build what we think is the world's leading data access technology to take advantage of that core foundation.
And what are those data access technologies?
One is key-value for caching solutions. The second is a SQL-like query language for JSON which we call NIQL ("nickel"). We take all the familiarity of the legacy query language that every developer in the world knows, and enable them, with those tools on top of a flexible data architecture. That, essentially, lowers the barrier to entry to the new capabilities that are provided by a NoSQL solution but with a toolset that they are used to from the past.
In addition to those, we have provided new capabilities like full-text search, and we are adding operational analytics to the platform so that application developers, and their surrounding teams, can access the underlying data in the unstructured format. That means you have all the benefits of the flexible data schema, but you also have the tools to query and derive the analytics from the underlying dataset.
Because of our core architecture it is very important to our customers, who are deploying applications, that they can do that in near real-time speed. So, when we think about the capabilities that we have layered together inside of our data platform, we're unlocking the power of NoSQL, but doing so in a way that enables application developers to very quickly learn the platform, and help them become efficient in picking up applications to take advantage of it.
Now, that core platform can run at any point in the cloud -- everything from the major public cloud to customer's private data centres -- and it can also run on premise. Now we've extended the power of the platform out to the edge. We have a solution that we have called Couchbase Lite.
This is small enough that it can run inside an application on a mobile device, and you still get the full power of the platform, including the data structure and our ability to query and, very soon, you will be able to run operational analytics on top of that.
We've built the synchronisation gateway that connects everything from the public cloud out to the edge, and everything in between. And it has orchestration and data movement technologies that give operations and applications teams global flexibility to bring applications to the user as opposed to trying to bring all of their data back to a central depository.
And that's where we've been able to create next-generation applications where people can get the benefits of the data that's in their hands, on a near real-time basis.
Can you take me through a customer example of how all this works?
Tommy Hilfiger is a very interesting use case. One of the things they are trying to do is revolutionise the fashion industry. One of the ways they are trying to do that is by creating, what they call, a Digital Showroom.
If you can envisage a new kind of shopping experience where you walk into a Digital Showroom and instead of going through racks of clothes, the system can be interfacing with high-definition screens where you can see all of the clothes and look at things like price, buying history, delivery dates and the like.
You can customise the shopping experience and all in a digital format that is understanding what kinds of merchandise best meets your needs.
What Tommy Hilfiger is trying to do is create an experience that is consistent with their overall brand. The company has rolled this out to 25 branches around the work but what's interesting is that they have reduced their operating expenses by reducing the number of samples they need to have.
None of this would be possible if you did not have a data platform that was able to, on a real-time basis, manage inventory, understand buying preferences, and create that customer experience.
At the same time, you've got to have connectivity back to a central repository in a cloud environment where you have an aggregation of all of this information that ties together the various digital showrooms back into their core operating systems, and manages their supply chain and ordering and customer information.
How about reliability?
Yes, that's a big part and it's part of our core-value propositions. When we say we have an architecture built for the enterprise, you can imagine that for Tommy Hilfiger, a customer deployment like that is mission critical for their business. Reliability, performance and scalability are things that we're manically focused on as a company so that we can stand behind our customers with confidence.
And other companies?
In the world of athletics, one of the current, significant challenges facing sports medicine is concussion diagnostics and therapy.
SyncThink is a company that has leveraged the Couchbase data platform and has combined that with a virtual-reality-type deployment on an end point that allows them to diagnose concussion -- on a near, real-time basis -- on the sideline of an athletic field.
They have a proprietary solution that uses eye-tracking technology to determine the health of a human brain.
SEE: IT pro's guide to GDPR compliance (free PDF)
Imagine a situation where you bring an athlete off the field who may, or may not, have a concussion. They strap on a virtual reality headset and use that eye-tracking to determine how injured the athlete's brain may or may not be.
Our system can help in a way that no other system can because the Couchbase data platform can be running in that local device and then have connectivity back to a central cloud repository where it's managing the aggregation of all customer information about the results of the diagnostic.
And there can be massive amounts of information that you need to be processing on a real-time basis.
How does your product compare with a product like MongoDB?
When you look at the world of databases, customers often have multiple solutions to match the various workloads and applications that they are optimising for.
The point of differentiation that Couchbase has chosen is mission-critical applications in the enterprise. And where we are uniquely positioned is in our ability to scale, perform at scale and do so reliably.
How big can we scale? We have customers who are performing millions and millions of operations a second.
RECENT AND RELATED COVERAGE
HarperDB's recipe for success seems so unlikely, it makes you wonder whether it's genius or just crazy.
Born during the post-Y2K backlash that gave rise to innovations that are now the cornerstones of big data implementations, Cassandra has firmly entrenched itself as one of the most popular databases.
MemSQL wants to be the world's best database. Leading that race is a tall order, but the new version seems to improve on an already strong offering.
How Amazon helped bring NoSQL to the enterprise mainstream (TechRepublic)
Amazon Dynamo started out as an internal itch that helped kick Amazon kicks its RDBMS habit. Here's how it could do the same elsewhere.
While it has become fashionable for operational databases to become multi-model, MongoDB has stuck to its knitting but in 4.0 release, it addresses some checkboxes on widely different sides of the database spectrum.
The emergence of multi-model databases providing developers multiple paths through and APIs is the latest evidence that databases take on multiple chores.
The social media time capsule was hacked July 4.