HTAP - Hybrid Transactional and Analytical Processing, Next Big Thing in Big Data

Changing Market Dynamics
Digital Transformation and Business applications are becoming social, mobile and real-time and driving the need for new Data Frameworks. Currently businesses deploy silos of Operational (OLTP) and Analytical (OLAP) datastores. This forces Data movement and data duplication, between OLTP and OLAP systems which results in latency which is not acceptable and Capex and Opex costs for several different copies.  For Businesses, Real-time context has more value than historical context. According to recent market study - 1TB ETL/day (initial copy + 3 derivatives) costs over $8M over 4 years, for an organization. This is driving the need for convergence of Operational and Analytical datastores.
 
Need for a new approach
Business leaders are looking at new approaches to deal with these changing market dynamics. This change is giving rise to a multi-modal architecture, which analysts (Gartner, Forrester)  call HTAP or Translytical DB. In simple terms, this means the ability to extract value from real-time data streams, by using real-time streams and historical data as a point in time reference. Key enabler of HTAP has been in-memory like performance and operational readiness, however there are other challenges. Find out how traditional Database vendors and new SQL on Hadoop vendors are solving this challenge for the following use cases:

•  Online transaction processing
•  Hybrid transactional and analytical processing
•  Data warehousing
•  Internet of Things and
•  In-memory database
   

Shailesh is responsible for CloudFabrix's Product vision, Marketing, and strategy for Data Observability and AIOps market. CloudFabrix is a Data Intelligence and Automation company. Shailesh is focused on evangelizing and extending the use cases for transformative "Robotic Data Automation Fabric" to unify Observability, AIOps and Automation across the edge and cloud.