Meet backup SLAs
Reduce backup windows with incremental-forever and app-consistent backups.
An agentless approach delivers performance and scale in a single solution.
Reduce backup windows with incremental-forever and app-consistent backups.
Instantly search for and recover objects at a granular level to any snapshot point in time.
Minimize your data footprint with data-aware deduplication, compression, and erasure coding.
Simple and automated protection for a wide range of NoSQL and Hadoop application data sources helps you gain speed, efficiency, and greater ROI.
A cloud data management platform for securing and managing enterprise data no matter where it lives.
Simplify and accelerate backup and recovery of enterprise workloads across on-premises and cloud with a secured unified platform for data resilience.
NoSQL, which stands for “not only SQL”, is a type of distributed database designed to handle and manage large volumes of unstructured or semi-structured data. It’s a non-relational database system that provides a flexible and scalable approach to storing and retrieving data, making it well-suited for big data and real-time web applications. NoSQL databases are known for their ability to handle large amounts of data and provide high availability and scalability.
The specific backup procedures may vary depending on the Hadoop distribution and the tools used, so we recommend consulting the documentation and best practices provided by the Hadoop distribution you’re using. Still, these tools provide basic backup capabilities and may not meet an organization’s recovery point (RPO) and recovery time (RTO) objectives. Protecting distributed databases is more important than ever and organizations require a new approach to understand the nuances of these modern workloads. Cohesity provides a data protection and management solution that solves challenges in navigating data magnitude and dynamism while facilitating consistency and security across your NoSQL and Hadoop workloads.
Building a Hadoop backup and recovery strategy involves careful planning and consideration of the unique characteristics of Hadoop’s distributed architecture. Rapid adoption of Hadoop within the enterprise has resulted in the deployment of a number of haphazard, quick-fix Hadoop backup and recovery mechanisms that may seem to work on the surface, but they often put your data and organization at significant risk, thus falling short. A proper, well thought out Hadoop backup and recovery strategy is needed to ensure that data can be recovered reliably and quickly, and that backup operations don’t take up too much engineering or DevOps resources.