Over a million developers have joined DZone.

Continuuity, the PaaS of Big Data

DZone's Guide to

Continuuity, the PaaS of Big Data

· Big Data Zone ·
Free Resource

How to Simplify Apache Kafka. Get eBook.

When Continuuity came out of stealth recently I was a little dismissive of a press release that was full of buzzwords and lacking significant details about what they’re actually doing. To their credit the Continuuity team reached out to me and spent some time talking about what they’re seeing in the marketplace and why they believe their approach to Paas is indeed relevant. To recap, Continuuity was founded around a year ago and, since that time, have been beavering away in stealth mode to build their product, funded from a seed round by Andreessen HorowitzBattery Ventures, and Ignition Partners. Coincidentally Continuuity is this morning announcing a $10M Sries A round – that in itself is ground to revisit what the company is doing.

Alongside the A-list VCs, Continuuity is founded by a team with real world experience of building big data applications at scale – Todd Papaioannou was Chief Cloud Architect at Yahoo! while Jonathan Gray is a former Facebook HBase guru. The Continuuity vision is to do for big data streams what the force.com platform did for customer data. Allowing people to take rich streams of information (in Continuuity’s case, big data) and build applications on top of it. The perspective they bring is that the barriers to entry for big data apps are almost insurmountable. Big data leverages a bunch of predominantly open source components – Hadoop, HBase, Hive, Pig, etc – but tying together these components is complex and difficult. Continuuity may mitigate this complexity by providing a pre-integrated big data platform on top of which customers can build apps.

They see four specific use cases for the Continuuity platform:

  • Getting data in – event ingestion, data queuing and a core transaction engine
  • A more traditional PaaS view of application containers- developers write code, package it up and deploy
  • Ready established datasets – collections of data, stored down in the infrastructure with a higher level API. Continuuity provides some data aligned with common patterns in apps – time series, counters etc
  • Data out- queries, via RESTful APIs and  utilizing both preconfigured and self-built user stored procedures

A good example of the sort of application being built on Continuuity is consumer intelligence applications – organizations can use Continuuity as an internal platform and, by using reusable policy driven permissions, create a kind of “internal data broker” were people can share and swap data and then built applications on top of that data.


After my initial concerns, my chat with Continuuity has shown there is a real value in what they offer – by providing an SDK and a set of high-level APIs that sits on top of a fabric layer that connects all the different big data components in an optimal way – they’re delivering on the promise of making big data accessible to all.

The interesting this is the tension between open source (after all the Continuuity fabric is created from a host of open source products) and the lockin that using glued together components creates. Continuuity does something to allay these fears by having a twin strategy – they provide high level abstractions but also provide low level APIs that customers can use. While they dissuade people from using those lower level APIs, the very existence of them go some way to allaying concerns around lockin. Alongside this Continuuity has plans to open source parts of their platform. There is an interesting opportunity here for Continuuity to do what Cloud Foundry has done for “regular” PaaS, by open sourcing the product, an ecosystem develops. How this would look in the Continuuity context however is less clear.

If Continuuity is ultimately successful – they will further reinforce the contention of greater value existing with an aPaaS as opposed to iPaaS approach (for more on this discussion, see my previous post here). Continuuity could argue that iPaaS (Heroku, EngineYard, Clodu Foundry) are all dumb and it is only through the enablement of high level applications through aPaaS that real value can be driven – time will tell with that regard.

Big data, despite being a buzz word, is an area of real potential. With real skills in building big data apps hard to find, Continuuity is on to a good thing.

12 Best Practices for Modern Data Ingestion. Download White Paper.


Published at DZone with permission of

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}