treefin Helps Users Optimize Their Finances with DataStax EnterpriseAugust 24, 2016
This post is one in a series of interviews with companies using DataStax Enterprise (DSE), featuring Killian Koller, CTO & Co-Founder of treefin AG.
DataStax: Hello Kilian, thanks a lot for your time today. Could you please tell us a bit about treefin? What exactly do you offer and what is your role there?
treefin: treefin is a personal finance app in which the user can get an integrated view on his banking, investments and insurances. Further, we try to assist users in optimizing their financial product portfolio. I’m the CTO covering all the technical and data analytical topics.
DataStax: What makes your digital finance assistant successful? What differentiates treefin from similar applications?
treefin: The main advantage of treefin is the integration of all relevant parts of one’s financial situation. Most other offerings only focus on one of the three main topics – banking, investments and insurance.
DataStax: Did you use a different technology before you started using DataStax Enterprise?
treefin: No, first time right with DSE ;-]
DataStax: Why did you decide to use DataStax Enterprise? What kind of data is stored there?
treefin: We primarily handle time based data like bank account turnovers, user events, etc. DataStax Enterprise was the perfect fit for this use case. We also wanted to build on a technology that could scale out with a growing user base, not having to change technology later on.
DataStax: How would you sum up the benefits you’ve achieved with DataStax Enterprise (DSE)?
treefin: The main aspect was a shorter time to market, not having to build the whole data storage and analytics stack ourselves.
DataStax: What caused you to use DSE over open source Cassandra?
treefin: The integration with Apache Spark™, OpsCenter as well as the possibility to rely on support from DataStax in worst case scenarios.
DataStax: What features from the DataStax Enterprise (DSE) stack are you using at the moment? What business use case do they fulfill?
treefin: Cassandra, Spark and OpsCenter which covers all our data storage and analytics requirements.
DataStax: Tell us about the future of your project. Do you intend to leverage other parts of DSE to make it a reality?
treefin: At the moment, we are working on several machine learning topics and also evaluating Spark machine learning (ML).
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