The eXtremeDB Financial Edition DBMS Platform
eXtremeDB Financial Edition benefits from a highly optimized and scalable underlying embedded in-memory database system (IMDS) design with rich developer tools.
In-Memory Database System (IMDS)
eXtremeDB Financial Edition stores data in main memory to eliminate performance-draining I/O, cache management, data transfer, and other sources of latency. (Persistent storage can be added for selected record types – for example, when managing historical data; but an IMDS is ideal real-time data).
eXtremeDB runs entirely within the application process, eliminating inter-process communication (IPC) between client and server modules.
Short execution path
A minimal code path speeds execution by reducing the number of CPU cycles required per database operation and increasing the likelihood that code needed for an operation is already in L1/L2 CPU cache.
The 64-bit eXtremeDB platform is proven managing terabyte-plus databases with billions of rows entirely in memory; persistently stored data scales to OS file system limits. Choose between transactions managers to scale predominantly read-only and predominantly read-write and/or clustered applications.
eXtremeDB Financial Edition provides numerous tools to boost developer productivity and maximize reliability and performance of real-time capital markets applications. These include:
Multiple APIs. For the lowest latency, applications typically access eXtremeDB Financial Edition using its fast, native navigational C/C++ API. The product’s SQL implementation includes an ODBC API; a more succinct and easier to use proprietary interface; and a type 3, version 4 JDBC driver. Also provided are native Java and C# (.NET) APIs.
Market data enhancements. Developers use eXtremeDB Financial Edition’s optional columnar layout to efficiently organize trades, quotes and other time series data, and vector-based statistical functions to accelerate financial calculations.
Choice of indexes. Supported indexes include standard B-trees, hash indexes, KD-trees for multi-dimensional data and Query-by-Example (QBE), custom indexes and more.
Performance monitoring interface. GUI-based performance monitoring enables users to zero in on key metrics when fine-tuning to reduce latency. Performance metrics are also provided via an API, so developers can build this capability into applications, with their own GUI. (See a screen shot of the performance monitor.)