TransLattice Releases Geographically Distributed RDBMS

Elastic Database is a high-performance, distributed SQL database for business-critical applications that improves reliability while reducing costs.

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TransLattice has released TransLattice Elastic Database (TED), a geographically distributed relational database management system (RDBMS).

A power outage or catastrophic event can wipe out an organization¹s IT operations in an instant. Backup data centers can give organizations a false sense of security, as failover doesn¹t always work and recovery often takes far longer than anticipated.

Geographical distribution of data -- including relational data -- is the future of computing for enterprises and the cloud, offering vast improvements in system availability, improved performance for remote users, effortless scalability, and data location compliance. By geographically distributing data, the system continues to work even if some nodes are down, greatly reducing the risk of a costly outage.

By distributing data to an organization¹s geographic locations, the TransLattice Elastic Database creates a highly available, fault-tolerant data fabric comprised of multiple nodes. With TED, a single database can run on multiple TransLattice nodes wherever it is needed, providing enterprise availability, strong performance for remote users, and easy scalability at less cost than traditional databases. Further, TED enables companies to comply easily with data jurisdiction requirements through policy.

TED’s fault-tolerant database fabric is comprised of multiple nodes and can be administered from anywhere on the network -- with no downtime -- by distributing data across geographic locations. It puts mission-critical data closer to the edge of the network for improved response time for customers, partners, and employees.

Nodes can be added on demand with no downtime. Nodes can be virtual machines, cloud instances, TransLattice appliances, or any combination thereof.

TED controls data location through simple-to-configure policies, thereby reducing the need for data federation and streamlining systems management.

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