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Distributed Query Processing

eXtremeDB offers different distributed database options to address different objectives.

eXtremeDB accelerates performance with distributed query processing.

How it works

With this capability, eXtremeDB for HPC partitions, or shards, a database and distributes query processing across multiple servers, CPUs and/or CPU cores. Sharding accelerates performance — dramatically, in some cases — via parallel execution of database operations.  This feature delivers high availability via failover, and harnesses the capabilities of many host computers rather than just one.

The benefits of distributed query processing are evident in McObject’s recent STAC-M3 benchmarks with partners E8 Storage, IBM and Lucera Financial Infrastructures.  In these tests, the eXtremeDB database was partitioned horizontally across up to 128 shards, resulting in record-setting performance managing tick data.

Distributed queries also allow far faster processing because they can perform parallel execution on each shard. The following diagram illustrates how the eXtremeDB xSQL engine and a distributed SQL client application might implement sharding.

Learn how sharding distributes query processing across multiple servers to ensure high scalability and low latency in our online documentation.

Review a table of the eXtremeDB distributed database options and objectives


Read a list of features to look for in a faster database management system


Learn more about eXtremeSQL

See a list of eXtremeDB audited record-breaking benchmarks

Distributed query processing chart copyright McObject

Designed for speed and efficiency

eXtremeDB for High Performance Computing and Big Data is based on a blazingly fast storage engine delivering scalability, low latency and advanced analytical capabilities for HPC workloads. eXtremeDB for HPC offers:

Record-setting performance year after year. Review our audited benchmarks

Parallel execution of database operations for systems that can’t afford to fail.

A highly efficient in-memory database system (IMDS) design that removes the I/O, cache management, data transfer and other sources of DBMS latency.

A combination of row-based and column-based layouts, in order to best leverage the CPU cache speed for time series data

For historical or OLTP data, eXtremeDB offers a wide array of performance-enhancing features, such as pre-warming the cache, cache prioritization, and many more.  Read about it in Inside HPC, or see for yourself with free evaluation software

What makes eXtremeDB for HPC different from other databases that also claim they are fast?

Many database systems include one or two of the performance-enhancing features mentioned so far, such as in-memory data storage, columnar data handling, as well as high performance SQL, and a short execution path. But you’d be hard-pressed to find all of them in one database system, and solutions offering some of these features may also lack “real” database capabilities such as ACID transactions. In contrast, eXtremeDB offers all of them plus a rich assortment of additional development and run-time features (our key features list is a good place to see the breadth of eXtremeDB’s capabilities).

Equally important, with new NoSQL solutions and databases cropping up so frequently, McObject’s eXtremeDB is a proven technology. McObject can point to a track record of 19+ years and over 30,000,000 successful deployments of the database system, in demanding financial technology as well as in mission- and safety-critical applications ranging from aerospace systems to smart grid, defense, consumer electronics, industrial control and telecom/networking infrastructure. View a partial customer list.

Row and columnar data layout can be combined in hybrid data designs to optimize performance managing mixed data.

Pipeline data with a rich library of vector-based statistical functions.

Learn about eXtremeDB for Big Data and Analytics