Hybrid Transactional/Analytical Processing (HTAP)

Hybrid Transactional/Analytical Processing (HTAP) is a term used to describe the capability of a single database that can perform both online transaction processing (OLTP) and online analytical processing (OLAP) for the purpose of real-time operational intelligence processing. The term was created by Gartner, Inc., a technology research firm.[1][2][3]

Background

In the 1960s, computer use in the business sector began with payroll transactions and later included tasks in areas such as accounting and billing. At that time, users entered data, and the system processed it at a later time. Further development of instantaneous data processing, or OLTP, led to widespread OLTP use in government and business-sector information systems.[4]

OLAP covers the analytical processing involved in creating, synthesizing, and managing data. With greater data demands among businesses, OLAP also has evolved. To meet the needs of applications, both technologies are dependent on their own systems and distinct architectures.[1][4] As a result of the complexity in the information architecture and infrastructure of both OLTP and OLAP systems, data analysis is delayed.[1]

HTAP Advantages and Challenges

Recent advances in research, hardware, OLTP and OLAP capabilities, in-memory technologies, and products enable transactional processing and analytics, or HTAP, to operate on the same database.[1][2][4] HTAP solves the issue of analytic latency in several ways, including eliminating the need for multiple copies of the same data and the requirement for data to be offloaded from operational databases to data warehouses.[1][2]

Most HTAP applications can be enabled by in-memory technologies that can process a high volume of transactions and offer features such as forecasting and simulations. HTAP has the potential to change the way organizations do business by offering immediate business decision-making capabilities based on live and sophisticated analytics of large volumes of data. Government and business leaders can be informed of real-time issues, outcomes, and trends that necessitate action, such as in the areas of public safety, risk management, and fraud detection.[1][5]

Some challenges for HTAP include limited industry experience and skills, as well as undefined best practices.[1]

HTAP functionality is offered by database companies, such as Apache Ignite/GridGain In-Memory Data Fabric, SAP HANA,[6][7] MemSQL, VoltDB, NuoDB, OrientDB, DataStax, and BlobCity.

References

  1. 1 2 3 4 5 6 7 Pezzini, Massimo; Feinberg, Donald; Rayner, Nigel; Edjlali, Roxane. "Hybrid Transaction/Analytical Processing Will Foster Opportunities for Dramatic Business Innovation." Gartner. Jan. 28, 2014
  2. 1 2 3 Wolpe, Toby. "SQL and NoSQL? Fine, but how does the hybrid database fit in?" ZDNet. May 12, 2014
  3. ↑ Conn, Samuel S. "OLTP and OLAP Data Integration: A Review of Feasible Implementation Methods and Architectures for Real Time Data Analysis." Regis University School for Professional Studies. Accessed Oct. 16, 2014.
  4. 1 2 3 Bog, Anja. Benchmarking Transaction and Analytical Processing Systems: The Creation of a Mixed Workload Benchmark and Its Application Springer-Verlage Berlin Heidelberg. 2014
  5. ↑ Baer, Tony. "Fast Data hits the Big Data fast lane." ZDNet. April 16, 2012
  6. ↑ Review, CIO. "Internet of Everything and Hybrid Transactional Analytical Processing". CIOReview. Retrieved 2016-03-26.
  7. ↑ "Gartner Reprint". www.gartner.com. Retrieved 2016-03-26.
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