December 14, 2017



For partnerships in the tech space to work, the products being paired need to enhance one another and really create synergy.

While we see many partnerships of technology, many falter or aren’t really going for synergy. Often they are joint marketing efforts in support of integrations that may have some benefit, but are hardly transformational. But one such pairing that I think will thrive and truly create synergy based on complementary functionality is the recent partnership between C3 IoT and MapR. This partnership makes sense because it is based on clever exploitation of the concept of the data fabric, a new layer of the technology stack that significantly extends the concept of a database to help manage the reality of having overwhelming amounts of data of different types from numerous sources. Companies and organizations are looking to wring the value out of all that data through AI.

Recently, I spoke with Ed Abbo, CTO of C3 IoT, and Crystal Valentine, Vice President of Technology Strategy at MapR, about their companies’ recent decision to team up. The partnership illustrates both the importance of establishing a data fabric, and how tech partnerships, when done right, can offer customers added benefits that are not possible with a single product alone.

Why This Partnership Occurred

For those unfamiliar with these companies, a little background might be helpful. MapR is a company breaking new ground implementing what is being called a data fabric. As I wrote about in a previous article on MapR, the data fabric is a new type of abstraction layer to manage, store, and integrate data across a scale-out cluster of servers, often in multiple locations. Within this fabric, data can be moved and processed in real-time and allows for:

  • The ability to store and retrieve data from many types of repositories, including NoSQL, streaming, and object storage
  • The ability to search across all repositories
  • Access to all of these repositories using a single method or API
  • Applying real-time analytics to the data across all these repositories
  • Integration of the data within these repositories

This type of data fabric layer is crucial to support new requirements from emerging applications focused on customer engagement, which need all the data about a customer. Increasingly, operational applications have the same need for 360-degree data integration. The data fabric essentially replaces the database layer of the application stack. Instead of requiring the application itself to handle all of these tasks, the data fabric layer handles it for the application.

MapR moves beyond these foundational capabilities in their approach to the data fabric. They have combined all of the essential capabilities of the data fabric so that an application can handle all data, including real-time, streaming data. But it can also handle data from any source or repository, including SQL data, and do so at scale, integrating large volumes of data, including data from microservices. Users can then search this data from a single location, regardless of its original repository or form, and then, crucially, they can replicate the data easily, with a consistent global name space across the entire reach of the business (even an international one), in a way that preserves the consistency of that data. That is the power of MapR’s data fabric.

C3 IoT: Accelerating Creation of Predictive, Data-Intensive, High Leverage Applications

C3 IoT, on the other hand, is dedicated to creating new forms of applications that help companies across industries make use of rich streams of data and tame the complexity inherent in the voluminous data generation from massive numbers of sensored assets and devices (also called the Internet of Things). C3 IoT also helps companies then discover important signals within that data, using embedded machine learning capabilities, and allows those signals to be acted on either by human intervention or through an automated response.

Many companies are striving to take advantage of step changes in technology, elastic cloud computing, AI, Natural Language Processing (NLP) and IoT, to rethink company operations from customer engagement, product design, and manufacturing through logistics and supply chains. This phenomenon, referred to as digital transformation, impacts all industries – healthcare, manufacturing, aerospace and defense, government, banking, insurance and retail. To help organizations accelerate digital transformation, C3 IoT offers a Digital Enterprise Platform.

C3 IoT implements a model-driven architecture, C3 IoT’s Type System, to create a logical abstraction of entities and processes the business cares about – including divisions, customers, physical things, systems, and business processes – which greatly assists businesses operating in complex environments. These virtual representations, C3 Types, are reusable across the business. C3 Types can aggregate data in real time from internal and external systems as well as sensors, unify those data, and process it using sophisticated machine learning. From there, businesses can run predictive and prescriptive applications to unlock business value from complex corporate environments.

C3 IoT allows these applications to be built up to 100 times faster in simple, low code ways so that companies can put a lot of data to work and take advantage of all the automation that is possible. In this context, C3 IoT recognized it needed a data fabric to help accelerate the ability of its application platform to solve the problems it aims to address across so many areas.

“Companies are struggling to develop and deploy AI and IoT-based applications,” Abbo said. “In some cases, they have identified tens to hundreds of apps and microservices that leverage AI, enterprise, sensor, and Internet data. What C3 IoT has done is develop an application development and operating platform that trivializes data aggregation from a multiplicity of data sources in real time and presents it in a uniform way through the C3 Type System so that companies and their IT organizations can rapidly deploy AI and IoT applications to, for example, improve customer engagement and product reliability, detect fraud, identify product quality issues early, forecast demand and predict supply and logistics disruptions, and optimize inventory. These applications radically transform business.”

Read the full article on Forbes here.