Combining Transactional and Analytic Databases

With many current systems failing to make data available in a timely manner, a significant share of companies are actively evaluating new forms of database management system (DBMS) technology, according to a recent survey from InterSystems. The resulting report, “Choosing a DBMS to Address the Challenges of the Third Platform,” indicates that much of the problem is based on the management of data that is transactional (records-oriented processing that drives business operations) versus analytical (data from many transactional databases and optimized for query speed). Supporting both types is difficult, as databases optimized for transactions are not usually able to perform complex analytical queries in a timely manner, if at all. At the same time, databases intended for analytics are frequently too slow at transaction processing to meet organizational needs. In addition, large amounts of transactional data move forward using extract transform load (ETL) technology, which migrates data to analytical databases too slowly, findings claim. “The era of digital transformation … brings with it the need to analyze an array of data types and to analyze transactional data at near-real-time speed,” according to the report. “Many organizations today are still using ETL data transfer approaches, which cannot meet requirements for real-time data analysis. Untimely data significantly inhibits [the] ability to compete and remain agile. A solution to these challenges is to consolidate database operations combining transactional and analytic capabilities in a single DBMS solution with blended features.” Professionals in 502 global organizations, whose work involves databases, took part in the research, which was conducted by IDC.