What is HTAP?
If you’ve been asking yourself this very question, then you will definitely benefit from our upcoming HTAP webinar series designed to address the evolving market requirements, challenges and recommended solutions surrounding big data analytics.
Our webinar series will relate to both concepts and include real-world examples of solution architectures leveraging a platform which tightly integrates in-memory computing and a high-performance Spark distribution for insight and action at the point of decision. You will learn about the “why” and the “how” of HTAP capabilities and how am HTAP platform can help you directly from GigaSpaces IMC division’s VP of Products and Strategy, Ali Hodroj.
HTAP is the cornerstone of modern big data architectures which mainly addresses the initial stage of fast data. Today, leading analysts are discussing how companies are incorporating technology to more readily generate actionable insights. Both Gartner’s HTAP (Hybrid Transactional/Analytical Processing), and Forrester’s Insight Platforms address how the industry is witnessing a convergence of workflows and technology platforms for real-time, analytics, cloud, and in-memory processing to effectively address time-sensitive business decisions that involve the volumes of big data.
HTAP described a new generation of in-memory data platforms that can perform both online transaction processing (OLTP) and online analytical processing (OLAP) without requiring data duplication. This concept of a real-time data pipeline can only exist in a world where the analytical workload is co-located with the transactional processing which is being executed on the same data. The result is that both analytical and transactional processing are being executed against one single source of truth of data, removing data replication out of the equation and increasing performance.
The need for HTAP arose when organizations realized that traditional architecture, which separates the data workflow between transactional and analytical systems, cannot respond to business requirements in real-time, but rather only provide after-the-fact analysis. Enterprises discovered that they were still holding back when it came to fully and meaningfully harnessing of their data due to limited experience, skills, and undefined best practices.
An HTAP architecture supports the needs of many new IoT use cases that require scalability and real-time performance. It enables instant decision making by bringing transactional data and analytics together at the time of the transaction. An HTAP architecture is best enabled by IMC techniques and technologies to provide analytical processing on the same (in-memory) data that is used to perform transaction processing.