eXtremeDB accelerates performance with distributed query processing.
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. Looking for additional options? eXtremeDB offers different distributed database options to address different objectives.
eXtremeDB for HPC was designed for speed and efficiency
eXtremeDB for HPC offers:
- Record-setting performance, year after year.
- A combination of row-based and column-based layouts, in order to best leverage the CPU cache speed.
- Parallel execution of database operations for systems that can’t afford to fail.
- An ultra-fast and flexible market data feed handler.
- A rich library of vector-based statistical functions.
- A highly efficient in-memory database system (IMDS) design that removes the I/O, cache management, data transfer and other sources of DBMS latency.
- 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.