While the volume of our data universe has grown exponentially over the past two decades, many companies struggle with underlying data infrastructure not designed or architected for high performance analytics at massive scale. This means that a database decision made 15 years ago could be impacting your ability to compete today and tomorrow. For many companies, that decision was to adopt PostgreSQL, an open source, ANSI SQL database.
In the beginning, most solutions would prove successful on PostgreSQL, but over time it has become clear that more muscle is needed. If your organization is struggling to achieve acceptable analytics performance with PostgreSQL hosting or regularly need PostgreSQL support, consider adopting a massively parallel processing (MPP) database like Vertica.
As with many data management deployments, the company experienced improved productivity and avoided additional hardware costs. However, Nimble Storage was also able to identify and close more deals with the Vertica Analytics Platform, shortening their sales cycle and automating many customer service tasks.
Over time, analytic data volumes will continue to soar. Companies with solutions on PostgreSQL (and similar entry-level or legacy platforms) need to make sure that they transition to a proven platform. Given the evolving yet strategic importance of the marketplace, the technical architecture for an analytic database platform should be, among other things:
The solution should be scalable in both performance capacity and incremental data volume growth. Make sure the proposed solution scales in a near-linear fashion and behaves consistently with growth in all of database size, number of concurrent users, and complexity of queries.
Designed for complex decision support activity in a multi-user mixed workload environment. Check on the maturity of the optimizer for supporting every type of query with good performance and to determine the best execution plan based on changing data demographics.
The solution should be manageable through minimal support tasks requiring DBA/system administrator intervention. It should provide a single point of control to simplify system administration.
|To be successful, analytic databases need to provide|
|Low long-term total cost of ownership|
|Excellent query performance and interactive usage|
|Ability to get to real-time feeds|
|A platform to support mixed, unpredictable workloads|
|A scalable path forward as data needs grow|