Case study

Vertica’s scalable and future-proof data analytics platform matches clients faster and more effectively

Challenge completely relies on data analytics for its online profile matching. Data analysis needs to happen in real-time so that candidates are matched swiftly and effectively. The company used a traditional database and Hadoop to store temporary data. Ramakrishnan Venkataramanan, Associate Vice President, Decision Support Systems, explains the challenges with the existing infrastructure: “As our business, and therefore our data, grows, our main problem was report processing time. This could take too long to deliver insights for dynamic decision making by our leadership team. New development was also slow, as the data warehouse was running 24/7. With these different technologies we needed multi-skilled staff which was hard to find. We would often have to train people ourselves.” wanted a scalable data analytics solution that would slot into their existing processes, at a minimum cost. The vision was a central data warehouse for all analytics and reporting purposes.


Ramakrishnan and team investigated all the options available, including Vertica, Greenplum and IBM Netezza. Vertica, on the other hand, performed well, giving the confidence to make the decision. liked the cost model proposed by Vertica, as explained by Ramakrishnan: “It was very straightforward, we just paid a single cost for the production server, and as this was calculated on a per TB cost rather than a per user cost, this worked well for us. We like that there are no hidden costs for things such as disaster recovery, which come as standard.”

With some hands-on support, including training, from Vertica, the production instance of the Data Analytics Platform was soon live. Because Vertica is very SQL-friendly, no reskilling of the team was required. As a result, the transition was smooth with a fast time-to-market. Ramakrishnan comments on the features that make daily life at easier for the team: “We love Vertica’s self-tuning capability. We just keep loading a large volume of data continuously each day, and Vertica takes care of tuning in the background without any intervention. Its massively parallel processing (MPP), columnar, architecture provides scalability and high performance queries on our large data volumes.”

Vertica leverages flattened tables with columns that get their values from querying other tables. Operations on the source tables and flattened tables are decoupled: changes in one are not automatically propagated to the other. This approach minimizes the overhead typically associated with conventional tables.

Vertica effectively integrates with Hadoop so that any requirements involving Hadoop data are copied using the Vertica Hadoop Reader.


Thanks to Vertica’s ease-of-use and smooth integration within the existing infrastructure, has experienced productivity improvements. Ramakrishnan comments: “We have already migrated 50 percent of our data warehouse to Vertica and we are focused on migrating the remainder as soon as we can. The results have been excellent. We deliver a high-performance service to our clients, with a cost-effective and scalable data analytics platform. Our management is pleased with the real-time reporting capabilities within Vertica.”

He concludes: “The support we received from Vertica throughout has been great. The team was always available and really responsive to any queries we had. We are also excited to see the future innovations within the Vertica platform. We want to explore machine learning and predictive analytics which will help us match our clients even better.”

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release-rel-2021-1-2-5675 | Tue Jan 12 21:44:14 PST 2021
Tue Jan 12 21:44:14 PST 2021