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==HTAP advantages and challenges==
There are various interpretations of HTAP other than Gartner's original definition; an "emerging architecture". These interpretations suggest different advantages, one being a database functionality. Recent advances in research, hardware, OLTP and OLAP capabilities, [[In-memory database|in-memory]] and cloud native database technologies,<ref>{{Cite web|url=https://azure.microsoft.com/en-us/blog/azure-analytics-clarity-in-an-instant/|title=Azure Analytics: Clarity in an instant|website=azure.microsoft.com|date=19 May 2020 |access-date=2020-06-20}}</ref> scalable transactional management and products enable transactional processing and analytics, or HTAP, to operate on the same database.<ref name=Pezzini /><ref name="Wolpe">Wolpe, Toby. [https://www.zdnet.com/article/sql-and-nosql-fine-but-how-does-the-hybrid-database-fit-in/ "SQL and NoSQL? Fine, but how does the hybrid database fit in?"] ZDNet. 12 May 2014</ref><ref name=Bog />
However, Gartner's most recent reports suggest broader advantages than a single unified database can offer. Traditional application architectures separated transactional and analytical systems. Digital business, and the need to respond to business moments, means that using "after the fact" analysis is no longer adequate. Business moments are transient opportunities that must be exploited in real time. If an organization is unable to recognize and/or respond quickly to a business moment by taking fast and well-informed decisions, then some other organization will, resulting in a missed opportunity (or a new business threat). HTAP allows advanced analytics to be run in real time on "in flight" transaction data, providing an architecture that empowers users to respond more effectively to business moments.<ref>{{Cite web|url=https://www.gartner.com/doc/3352419/enable-digital-business-innovation-hybrid|title=How to Enable Digital Business Innovation via Hybrid Transaction/Analytical Processing|website=www.gartner.com|access-date=2017-04-15}}</ref>
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Some challenges for HTAP include limited industry experience and skills, as well as undefined best practices.<ref name=Pezzini />
In 2020, the first paper in the industry was published by the team of [[PingCAP]] describing the practical implementation of a distributed Hybrid Transactional/Analytical Processing (HTAP) database: [[TiDB]]: A Raft-based HTAP Database.<ref>{{Cite journal |title=TiDB: A Raft-based HTAP Database |url=https://www.vldb.org/pvldb/vol13/p3072-huang.pdf |journal=Proceedings of the VLDB Endowment |volume=13 |issue=12 |pages=3072 |doi=10.14778/3415478.3415535 |s2cid=221666363 |issn=2150-8097}}</ref>
==References==
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