New financial version of eXtremeDB 6.0 features improved preview _ database other

Access vector based functions through SQL and Python to improve programming speed and productivity. Distributed query processing and the use of RLE compression to deal with large data analysis in the capital market.

Federal Road, Washington, October 27, 2014 –mcobject® announced that extremedb® Financial version 6.0 has been officially released, which is also an important upgrade to the capital market database system technology. The improvements include the use of widely used SQL and Python languages to access the most powerful features of the eXtremeDB Financial Edition, exploiting declarative SQL language and the fast prototyping Python language to unleash productivity. The 6.0 version uses its new features: Distributed query processing and professional market data compression to address the large data challenges facing the financial system, increasing the efficiency of processing real-time and historical data (more than one trillion data growth day). The founder and CEO of McObject said: "In STAC-M3 and other tests, the eXtremeDB Financial Edition has demonstrated the characteristics of ultra-low latency when it deals with market data." The 6.0 version has been improved on this feature, with some features that improve performance, others to increase revenue, and some new features to both. Many large companies in the capital markets have used the eXtremeDB financial version of the 6.0 version of the improved technology. McObject hopes that as the upgrade goes into full circulation, it will help more companies solve the most difficult challenges of financial computing.

Graves shows the specific improvements to the eXtremeDB Financial version 6.0, as follows:

Vector-based statistical functions implemented using SQL and Python

A notable feature of eXtremeDB is its vector based statistical function library. This statistical function library is passed to the CPU cache to shorten the latency when analyzing market data. The 6.0 version introduces the function of using its vector based functions from the intrinsic SQL, and SQL is the most commonly used database language in Enterprise computer technology. This has also greatly increased the developer population, whose existing technology can quickly adopt McObject database systems.

An application written in C + +, Python, Java, and C # (. NET) languages can use SQL through the command-line interface, and it itself can. It has a high level of productivity in creating interactive code with database systems, which makes development work faster in areas that are key competitive factors for some time. McObject video shows a practical example of using vector functions from internal SQL.

eXtremeDB Financial version 6.0 also supports Python. Python is a high-level language for fast algorithms (especially prototyping) that support capital markets. Using Python, coupled with extremedb Dynamic Data definition Language DDL, developers can quickly implement their ideas by testing the changes in the code, database tables and indexes for rapid optimization.

Distributed query Processing

Using distributed query processing, the eXtremeDB financial version divides the whole database into distributed query processing through multiple servers, CPUs or CPU cores. In some cases, using multiple hosts to perform database operations in parallel, the performance of the database will be greatly improved.

Market data compression

This upgrade adds a powerful compression algorithm that reduces the volume of stored market data, reduces storage costs, and speeds processing. This stroke length encoding (RLE) compression can be applied to columnar data (defined as the ' column ' database type of the eXtremeDB Financial edition, usually used for trading, quoting, and other market data) in McObject tests, after activating this function, The Chicago options Trading Market Volatility Index (VIX) of the pen data volume dropped to its pre-compressed volume of One-fourth, the database read speed also increased by 21%. eXtremeDB Financial version 6.0 also increases the ability to compress data that is not columnar.

Improvement of statistical function library based on vector

eXtremeDB Financial Edition 6.0 improves its vector based function libraries in a variety of ways, including:

  Many new features, including a whole family of ha-Hi aggregation, which can
  improve unordered sequences (that is, not filtered by timestamps and fixed intervals).
  Creates a sequence from an input string, as in the following example: Create a sequence named "Bid": "Insert the quote value (' {1.0, 1.1, 1.2, 1.1} ')"
  through a new SQL SELECT statement keyword, The column-like data (i.e. time series data, such as market data), is based on the row format.