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Datos IO RecoverX software, designed to protect scale-out databases running on public clouds, now allows query-specific recovery and other features to restore data faster.
RecoverX data protection and management software is aimed at application architects, database administrators and development teams. Built for nonrelational databases, it protects and recovers data locally and on software-as-a-service platforms.
Datos IO RecoverX works with scale-out databases, including MongoDB, Amazon DynamoDB, Apache Cassandra, DataStax Enterprise, Google Bigtable, Redis and SQLite. It supports Amazon Web Services, Google Cloud Platform and Oracle Cloud. RecoverX also protects data on premises.
RecoverX provides semantic deduplication for storage space efficiency and enables scalable versioning for flexible backups and point-in-time recovery.
More security, faster recovery in Datos IO RecoverX 2.5
The newly released RecoverX 2.5 gives customers the ability recover by querying specific tables, columns and rows within databases to speed up the restore process. Datos IO calls this feature "queryable recovery." The software's advanced database recovery function also includes granular and incremental recovery by selecting specific points in time.
The latest Datos IO RecoverX version also performs streaming recovery for better error-handling. The advanced database recovery capability for MongoDB clusters enables global backup of sharded or partitioned databases. The geographically dispersed shards are backed up in sync to ensure consistent copies in the recovery. Administrators can do local restores of the shards or database partitions to speed recovery.
RecoverX 2.5 also supports Transport Layer Security and Secure Sockets Layer encryptions, as well as X.509 certificates, Lightweight Directory Access Protocol authentication and Kerberos authentication.
Dave Russelldistinguished analyst, Gartner
Dave Russell, distinguished analyst at Gartner, said Datos IO RecoverX 2.5 focuses more on greater control and faster recovery with its advanced recovery features.
"Some of these next-generation databases are extremely large and they are federated. The beautiful thing about databases is they have structure," Russell said. "Part of what Datos IO does is leverage that structure, so you can pull up the [exact] data you are looking for. Before, you had to back up large databases, and in some cases, you had to mount the entire database to fish out what you want.
"With the granular recovery, you can pick and choose what you are looking for," he said. "That helps the time to recovery."
Peter Smails, vice president of marketing and business development at Datos IO, based in San Jose, Calif., said the startup is trying to combine the granularity of traditional backup with the visibility into scale-out databases that traditional backup tools lack.
"With traditional backup, you can restore at the LUN level and the virtual machine level. You can get some granularity," Smails said. "What you can't do is have the visibility into the specific construct of the database, such as what is in each row or column. We know the schema.
"Backup is not a new problem," Smails said. "What we want to do through [our] applications is fundamentally different."