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Diego Ferreira

Ekam helps organizations deliver competitive advantage with DataStax Enterprise

By Diego FerreiraNovember 14, 2016

This post is one in a series of quick-hit interviews with companies using DataStax Enterprise (DSE) for key parts of their business. For this interview, we talked with Dennis Paul, Founder and CEO of Ekam.

DataStax: Hello Dennis, thanks a lot for your time today. Could you please tell us a bit about Ekam? What exactly do you offer and what’s your role there?
Ekam: Ekam is the Work Platform that can deliver your business a huge competitive advantage by enabling everyone in the organization to connect seamlessly with both people and information and get work done, 100% of the time.

Not just working together within your organization, Ekam helps you work together with and even train, your clients and partners too, with all the intellectual property remaining within the secure perimeter of your business.

I’m the Founder and CEO of Ekam Labs where I provide overall vision for the platform besides wearing many other hats, typical of most startup CEOs.

DataStax: What makes your collaboration platform successful, what differentiates you to similar applications?
Ekam: Ekam “hyper-converges” almost all unstructured information in your business into one single platform, be it several modes of communication (chats, messages, email, phone calls and more), tasks, documents and files, enterprise social, crowdsourcing, e-learning, meetings et al.

This information is traditionally silo-ed in disparate stand-alone applications. Ekam hyper-converges all of that into a single, coherent data store.

Using the multi-model DSE 5.0 infrastructure in the backend, the Ekam Data Store is a real-time fingerprint of all the unstructured data within a business, inter-connected through a myriad of complex relationship maps, including people’s interactions with this organizational data. This sets up the data store as an enabler for a machine-learning driven experience that is personalized for each user. It also drives the delivery of a vastly superior search-and-discovery experience to the users.

In the front-end, Ekam delivers an integrated user experience, both in form and function. In form, the UX compares so well with today’s consumer apps. Functionally, communication, collaboration and information discovery are wired at every single user touch-point, all in the normal flow of work.

Ekam runs on the browser and on phones through native apps for iOS and Android.

DataStax: Did you use a different technology before you started using DataStax Enterprise?
Ekam: Initially, we built the Ekam application entirely on MySQL. We used REDIS for Chat and Apache Solr™ for Search.

DataStax: Why did you decide to use DataStax Enterprise? What kind of data is stored there?
Ekam: Honestly, our decision to move was driven more by what DataStax Enterprise offered, rather than by Apache Cassandra™ .

The initial trigger was our need to have end-to-end AES-256 encryption for all data in motion and at rest. While the RDBMS portion supported AES-256 encryption, we had problems getting there with our REDIS implementation of Chat as well as our Apache Solr™ implementation of Search. By moving to DSE, we were able to achieve end-to-end encryption for both Chat and Search.

However, once we dived deeper, we found several other areas where the data is better stored in DataStax Enterprise, instead of in an RDBMS.

At the moment, we are migrating the entire data store to the multi-model, graph plus columnar, and DSE 5.0 database.

DataStax: How would you sum up the benefits you’ve achieved with DataStax Enterprise (DSE)?
Ekam: Our vision with Ekam was to make the workplace way more efficient than it ever has been, by enabling everyone in the organization to connect seamlessly with both people and information and get work done, 100% of the time.

DSE helps us meet the original vision of our platform offering, especially with the ability to handle highly connected data that reveals both depth and breadth for the relationship between entities.

Being an enterprise-certified database, DSE helps our application platform to be enterprise class with respect to security, scalability, availability and performance.

DataStax: What caused you to use DSE over open source Apache Cassandra™?
Ekam: In our case, we went straight into DSE without so much considering Apache Cassandra™. We initially adopted DSE for a specific use case; end-to-end encryption.

However, today, there are so many things, including the Graph database that keeps us all so excited about DSE, over here at Ekam Labs.

DataStax: What features from the DataStax Enterprise (DSE) stack are you using at the moment?
Ekam: Integrated DSE Search with Live Indexing: This saves us from the heavy lifting otherwise required to integrate stand-alone Apache Solr™, both for development and for implementing it in a production environment.

End-to-end AES-256 encryption: including in the search index, document and file content.

Columnar Cassandra Data Store: With Ekam’s card-based UI design, we store all the data pertaining to a card in a single row in the DataStax Enterprise database. Compare this to data being stored instead in multiple tables and rows in a legacy RDBMS and information being retrieved using highly complex queries that have lots of joins.

The Graph Database: For us, this is the most exciting feature of DSE that helps us meet the original vision of our platform offering, the ability to handle highly connected data that reveals both depth and breadth for the relationship between entities.

DataStax: Tell us about the future of your project, do you intend to leverage other parts of DSE to make it a reality?
Ekam: At the moment, our focus is to leverage DSE graph, to build a holistic view of all the unstructured information within the enterprise. This information has traditionally been in silo-ed application repositories. DSE Graph enables us to meet the original vision of our platform offering with which we can now build the complete inter-connectedness of this data, including how people interact with this data.

With DSE Graph, we get a data store that can enable a machine-learning driven experience, personalized for each user. Combined with DSE Search, we can also deliver a vastly superior search-and-discovery experience to the users.

Once we meet our goals with respect to unstructured information within the enterprise, we intend to connect other realms of data, including more structured information, in a holistic manner.

DataStax: What advice would you give to other startups that are thinking about using DataStax Enterprise for the first time in their solutions?
Ekam: The columnar data store of DataStax Enterprise mirrors data as in real life unlike the more mathematical and complex relational database. Hence, designers and developers can easily relate to the DataStax Enterprise way of data management, so the learning curve is indeed way shorter than one would imagine.

Any startup building a solution today should have a serious look at DataStax Enterprise, before they even consider an SQL database.

The DataStax Enterprise version of Apache Cassandra™ makes your solution enterprise-ready at the outset, whilst giving a basket of other features like Live Search indexing, graph database and end-to-end encryption.



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