Innovating the Healthcare Industry with Liquid Grids and DataStax EnterpriseMarch 1, 2017
This post is one in a series of quick-hit interviews with companies using DataStax Enterprise (DSE) for key parts of their business. In this interview, we talked with Luis Valles, VP of Engineering at Liquid Grids.
DataStax: Hello Luis, thanks a lot for your time today! Could you tell us a bit about Liquid Grids and your role at the company?
Liquid Grids: Liquid Grids develops a technology platform for the healthcare vertical. It allows users to get insights about diseases and how they affect people around the world by gathering and mining user conversations from Social Media and Social Web. The insights can go very granular such as symptom, diagnosis, procedures, and treatments. Liquid Grids also has a marketing branch that uses the technology internally to build marketing campaigns for biotech and drug companies.
I’m the VP of Engineering and I also write code.
DataStax: What makes your healthcare-targeted platform successful and what differentiates you to similar applications?
Liquid Grids: First of all, we are the only company (aside from Treato) that is fully dedicated to healthcare, which gives us a substantial edge over the other platforms that are broader and/or multi-vertical. By this, I mean that other platforms try to address every vertical, but in fact, they are very shallow in each of those verticals, especially when dealing with healthcare, which requires really deep domain specialization of the technology. Secondly, unlike Treato, we don’t just provide insights, but also the ability to design, build and launch campaigns in multiple digital channels.
DataStax: Did you use a different technology before you started using DataStax Enterprise?
Liquid Grids: Yes, initially we used Postgres.
DataStax: Why did you decide to use DataStax Enterprise? What kind of data is stored there?
Liquid Grids: It was before my time, but from what I understand, Postgres could not provide even close to the performance that it was required for the type of Big Data (text data) that we gather.
The data stored is health-related posts from users all around the world as well as demographic information, geo information, etc.
DataStax: How would you sum up the benefits you’ve achieved with DataStax Enterprise?
Liquid Grids: The results from DataStax are impressive and exceedingly successful. DataStax Enterprise has offered us unprecedented performance, scalability, reliability and availability of the system.
DataStax: What caused you to use DataStax Enterprise over open source Apache Cassandra™?
Liquid Grids: Simplicity.
DataStax: What features from the DataStax Enterprise stack are you using at the moment?
Liquid Grids: Apache Solr™ integration, which gives us the ability to query with relative ease.
DataStax: What advice would you give other startups that are thinking about using DataStax Enterprise for the first time in their solutions?
Liquid Grids: DataStax Enterprise with Apache Cassandra™ and Apache Solr™/Apache Spark™ technologies with the Java combination allows you to build Big Data systems quickly without the long development life cycle of relational database design, complex query/transactions and so on. It is also much quicker and simpler than trying to go directly with the Hadoop ecosystem. Therefore, you can bring a product to market much quicker, which is vital for any start-up company. I’ve seen many startup companies that start using MS technology with .NET and SQL Server thinking that it is more flexible, easier to use and cheaper. These companies require huge funding and long development life cycles. SQL Server is a complex system not built for Big Data transactions and with poor scalability. The complexity of SQL and .NET requires a long process with bigger and highly technical staff that may include DBA, Data Modeler, ETL/SSIS developer, SQL Developers, etc. None of these roles may be necessary with DataStax Enterprise.
SHARE THIS PAGE