Key Benefits

Application-Centric Backup

  • Application-consistent point-in-time recovery
  • Scale-out software to meet backup and recovery requirements (RPOs and RTOs)
  • Built for scale with large sized clusters (hundreds of nodes)

Recover in Minutes

  • Fully orchestrated and granular recovery (column family level)
  • Single-click transfer with no repairs after recovery
  • Flexible recovery to the same or different clusters

Increase Ops Efficiency

  • 70%+ reduction in backup storage costs (deduplication and compaction savings)
  • Automated refresh of Test/Dev/QA environments
  • Ease of deployment with API-based architecture and native UI interface

Reference Architecture for Cassandra

The Challenge

In response to digital transformation requirements and explosive data growth, organizations are turning to scalable, distributed databases such as Apache Cassandra / DataStax to build next generation customer-centric applications. These applications require massive scalability without sacrificing performance, creating data protection challenges.

The Solution: RecoverX

Datos IO RecoverX is scale-out, elastic data protection software that delivers point-in-time backup and automated recovery for next-generation applications built on distributed NoSQL data sources including Cassandra. RecoverX leads to significant TCO savings for customers when compared with native solutions or any other tools.

Features and Benefits

Datos IO RecoverX is built to address the unique data protection requirements of database administrators (DBAs) and application developers building applications on Cassandra.

Data Management Architecture – CODR

  • Consistent Orchestrated Distributed Recovery patented cloud-first, scale-out, data management architecture
  • Uses elastic compute to autoscale application load
  • Transfers data in parallel to and from file-based and object-based secondary storage for multiple use cases, including data protection and testing and development
  • Backup data stored in native formats
  • Removes dependency on media servers

Flexible and Granular Backup

  • Application-consistent point-in-time (PIT) backup of Cassandra column families
  • User-specified PIT backup
  • Databases never quiesced during backup
  • Backup as frequently as every 30 minutes at any granularity

Semantic Deduplication – Single-Copy Restore

  • Application-aware semantic deduplication eliminates redundant data
  • Consistent data versioning enables complete data recoverability, portability, and mobility
  • Recover data at table-level or file-level granularity

Query-able Recovery

  • Industry-first feature allows maximum flexibility for recovery
  • DevOps or database administrators (DBAs) can recover exact columns and rows without recovering the entire column family
  • Near zero RTO
  • Refresh Test/Dev environments

Any Cloud: Private Cloud, Hybrid Cloud, and Public Cloud

RecoverX can be deployed on:

  • Physical server
  • Virtual machine
  • Cloud-native compute instance (i.e. AWS, GCP, etc)

Policy-Based Operational Management

  • Flexible data protection policies
  • Schedule backup policies at any granularity
  • Change existing policies including retention time
  • Pause/resume backup operations
  • Delete backup policies

Deployment Efficiency

  • Simple-to-use infrastructure
  • Only single virtual machine or cloud compute instance needed
  • Leverages native elastic cloud storage

Native Integration with Apache Cassandra

  • Operates at cqlsh level
  • Leverages APIs and other metadata information
  • Delivers full-feature backup and recovery

Data Protection Use Cases

Customers building applications on Apache Cassandra databases look for the following data protection use cases and associated features:

  • Backup and Recovery (collection-level and/or database-level)
  • Non-operational recovery use cases such as migrations and test/dev
  • Support for private cloud deployments both physical and virtual
  • Support for public cloud deployments including compute and storage services on AWS and GCP

Ready to become a data hero?