Couchbase, Inc. today introduced breakthrough scaling technology that substantially increases application performance and dramatically reduces costs. Multi-Dimensional Scaling provides the option to isolate database query, index and data services, so that hardware resources can be independently assigned and optimized on a per node basis, as application requirements change.
“Unlike MongoDB, Oracle, Cassandra, and other databases that have a limiting ‘one size fits all’ approach to scaling, Couchbase is enabling organizations to precisely provision hardware to meet application performance requirements,” said Bob Wiederhold, CEO, Couchbase. “With Multi-Dimensional Scaling, enterprises can independently assign and scale the index, query and data services to specific servers. This improves performance, reduces hardware costs, and enables enterprises to support a much broader set of applications with a single database: Couchbase Server.”
Multi-Dimensional Scaling: Isolate and Optimize Database Services
Until now, the query, index, and data services of a database typically share the same hardware and compete with each other for resources. This can result in expensive overprovisioning of hardware, and degraded application performance due to resource contention. Couchbase Server 4.0 with Multi-Dimensional Scaling eliminates these problems by enabling enterprises to run database services on separate hardware and assign right-sized servers for each service. Multi-Dimensional Scaling is configurable during runtime, giving organizations the ability to deploy one configuration at launch, and then change the scaling based on application performance needs. This new flexibility gives organizations powerful new control to ensure application performance and reduce hardware costs.
Every database service can benefit from Multi-Dimensional Scaling:
- Query: Query is a CPU heavy operation. In a distributed environment, a query is spread across many servers, resulting in a battle for resources that can degrade other database services. In particular, long-running or complex queries can severely impact performance. With Multi-Dimensional Scaling, enterprises can isolate the query service and assign to it a small set of low cost commodity servers or a large server with more computing power. This results in faster queries and avoids impacting other services.
- Index: Index service is disk intensive. Running an index across many servers in a large distributed environment results in slower indexing performance. Multi-Dimensional Scaling allows enterprises to isolate the index service so that index operations are performed only on the assigned hardware. This vastly improves index performance and enables enterprises to maintain multiple indexes without degrading read/write or query performance.
- Data: The Data service is relatively simple. It reads and writes the data and its primary requirement is to be fast. Keeping data in memory speeds data access. The optimal hardware to support fast reads and writes is a combination of memory and commodity servers. With Multi-Dimensional Scaling, enterprises can isolate the data service on low-cost boxes to maintain sub-millisecond read/write operations with no degradation from query or index services.
“Enterprises are faced with a broad range of data processing requirements, for which they have traditionally relied on extending the relational model and, more recently, combined a variety of specialist NoSQL databases,” commented Matt Aslett, research director, data platforms and analytics. “Our research suggests that enterprises are making strategic investments in more agile, multi-model databases that serve a variety of needs. Couchbase’s Multi-Dimensional Scaling appears to be an innovative, flexible, approach to supporting a wider range of data processing workloads.”
Multi-Dimensional Scaling will be available in Couchbase Server 4.0, scheduled for release in Summer 2015.