When a software-as-a-service (SaaS) company’s HBase database became so massive it was unable to perform Hadoop cluster backups, they turned to Pythian to find a robust and cost-effective solution.
A large SaaS company’s on-prem Hadoop cluster was used to store tens of thousands of audio files generated by their proprietary software, and the associated metadata. However, the company’s 215-plus terabyte Apache HBase database was so large it was unable to support the necessary snapshots long enough to perform Hadoop cluster backups. If the Hadoop Distributed File System failed, they were facing catastrophic data loss and a recovery process of several weeks if not months.
The company had previously attempted to fix the problem using Commvault, but there were too many cluster performance issues for this option to work.
They needed a robust and cost-effective BDR solution. Pythian was there to provide unbiased advice.
The client’s IT leadership was able to verify their assumptions through Pythian’s vendor-agnostic expertise. This empowered the team to make confident decisions about their technology choices.
12 hours or less to recover the last 12 months performance benchmark met
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