Clustrix’s nResiliency provides continuous database through synchronized multi-node failure



Clustrix, a vendor of scale-out relational database designed for the elastic scaling requirements of high-transaction, high-value workloads of web applications, announced last week its nResiliency feature which ensures that the database, and hence the application, remains available in the event of multiple simultaneous server or instance failures.

The new feature further ensures that the database, and hence the application, remains available in the event of multiple simultaneous server or instance failures. It also provides the ability to define the number of servers in the cluster that can become unavailable simultaneously while ensuring continuous database availability, so that it is easily configurable according to data sensitivity and criticality.

Currently available, nResiliency delivers confidence that data is safe and continuously available should two or even more servers (nodes) fail at the same time. Companies can now decide on the maximum number of nodes that could potentially fail in the cluster without losing any data, then ClustrixDB automatically generates the number of data replicas necessary to successfully recover, in the event of multi-node failure.

Clients can also deploy another cluster across geographies with asynchronous replication. Clustrix uses the MySQL replication protocol. For disaster recovery Clustrix offers fast parallel backup that takes the same time irrespective of number of nodes in the database cluster.

The addition of nResiliency follows Clustrix’s recent announcement that it has enhanced the database with In-memory processing for a three-times performance boost for certain workloads, full containerization for easy installation and deployment, and heightened security with AES 256-bit encryption.

 

ClustrixDB was developed to address MySQL’s scale limitations, but its architecture is distinct from other MySQL replacements in that it is designed to “scale out” both writes and reads by adding server nodes. This enables it to scale linearly to the point where there are almost no limits to the number of simultaneous transactions it can handle, with practically imperceptible latency to the end user.

Scale-out ability, combined with the new nResiliency protection against multi-node failure, means that companies can now easily scale to the demands placed on their application by millions of concurrent users.

E-commerce sites facing holiday shopping traffic; gaming companies launching a new title; consumer web services and social applications can now all freely match database capacity to demand. Easily add scale when you need it, and then scale-back when you don’t, only paying for the servers you need.

ClustrixDB provides even faster performance, combining the speed of NoSQL with the relational benefits of SQL for performance improvements of up to 300 percent for in-memory bulk data ingest, in-memory streaming HTAP, and high-volume aggregate processing; ability to store in-memory or on-disk without separate coding requirements; and automatic linear scalability to match growth by simply adding more servers.

Earlier this month, Clustrix partnered with big data security company Zettaset to transform data protection and privacy for companies that rely on large-scale OLTP databases. The benefits of the relationship are now available to customers who can seamlessly and securely deploy ClustrixDB 8.0 with the Zettaset Big Data Encryption Suite, to achieve the highest level of security, performance optimized for large-scale distributed computing and storage environments.

A drop-in replacement for MySQL, ClustrixDB powers some of the world’s most dynamic web applications with its scale-out, in-memory performance capabilities to ensure peak performance through heavy concurrent traffic. As the number of cyberattacks on online companies continues to rise, these sites also need to secure their customers’ data. The Clustrix/Zettaset partnership enables them to meet stringent security requirements without compromising either throughput or scalability.

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