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Companies are looking for a single database engine that can address all their varied needs—from transactional to analytical workloads, against structured, semi-structured, and unstructured data, leveraging graph, document, text search, column, key value, wide column, and relational data stores; on a single platform without the latency of data transformation and replication. They are looking for the ultimate database nirvana.
The term hybrid transactional/analytical processing (HTAP), coined by Gartner, perhaps comes closest to describing this concept. 451 Research uses the terms convergence or converged data platform. The terms multi-model or unified are also used. But can such a nirvana be achieved? Some database vendors claim to have already achieved this nirvana. In this talk we will discuss the following challenges on the path to this nirvana, for you to assess how accurate these claims are:
· What is needed for a single query engine to support all workloads?
· What does it take for that single query engine to support multiple storage engines, each serving a different need?
· Can a single query engine support all data models?
· Can it provide enterprise-caliber capabilities?
Attendees looking to assess query and storage engines would benefit from understanding what the key considerations are when picking an engine to run their targeted workloads. Also, developers working on such engines can better understand capabilities they need to provide in order to run workloads that span the HTAP spectrum.