Optimize Hadoop Operational Efficiency By 30%

As more organizations embark on data transformation programs, the Acceldata enterprise data observability platform is being put to use to help data teams derive maximum efficiency and ROI from their data stack. The problem is that without the right level of visibility, data environments keep adding new tools, more complexity, and more blind spots.

Acceldata Pulse Cluster Load Heatmap

Many organizations have invested heavily in mission-critical solutions built on the Hadoop ecosystem. Cloudera has announced the end-of-support for the legacy Hortonworks Data Platform (HDP) and Cloudera Data Hub (CDH). Organizations must assess the pros and cons of whether to migrate to the Cloudera Data Platform (CDP), modernize on alternative platforms (such as Kubernetes or cloud offerings), or go it alone with a self-support model.

Acceldata Pulse Performance Simulator

Fortunately, a fourth option exists, Acceldata provides a Data Observability platform and support services that give organizations running on-premises Hadoop more flexibility with lower risk and cost for their current and future big data environments. With then right approach to data observability, data teams can benefit from multiple advantages, including:

  • Risk is eliminated by receiving superior support from Acceldata for legacy Hadoop environments.
  • Timing is now on the customer’s side for deciding if and when migration occurs.
  • Cost can be significantly lower compared to the alternatives. Massive migration and re-engineering costs can be avoided. Acceldata support can be less than 50% of what Cloudera charges with superior service level agreements. Typically, infrastructure costs can be reduced by 10%-40% through efficiency gains enabled by the Acceldata Data Observability platform.
  • Talent requirements are eased as organizations can rely on Acceldata’s team of experts and extended support offerings that can include part-time or full-time site reliability engineers.