Yes yes okay we get it. Hybrid cloud is better than public cloud (with its openness and multi-tenant-ness) & better than private cloud alone (with its expandability that doesn’t ever match the breadth of public cloud) and that’s the way it shall always be, for now.
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But hybrid cloud on its own has implications — not least for software deployment concerns.
While the industry talks about hybrid deployment models, today’s transactional, operational and analytic data is typically managed in rigid silos, limiting performance and (some would argue) the option to get to actionable insights — this is not good for the new hybrid world.
Addressing ‘diverse data’
Tech vendors are aiming to address this issue and this is why we see firms like Actian position themselves specifically as ‘hybrid data management, analytics and integration’ specialists.
The firm’s Actian X product is claimed to be the first native hybrid database that combines the an OLTP database with a analytics query engine.
Rohit De Souza, CEO of Actian says that his firm embraces the entire hybrid data ecosystem, combining best-fit tools to bridge on-premise and cloud environments while also powering modern data-driven applications and services.
“Actian X brings the record-breaking performance of Actian Vector analytics into the heart of the OLTP database to effortlessly process transactional, analytical and hybrid workloads from a single database running on a single compute node,” said De Souza.
“Actian X’s common SQL language interface and management framework seamlessly deliver operational analytics and enable a new class of applications that can interleave OLTP and analytics queries on the fly,” he added.
What’s different here
What is (arguably) genuinely different here is that a huge number of data science, data engineering, data developer and data analytics software systems are tied to specific applications or are limited by available system memory.
As De Souza points out, hybrid data management integrates high performance analytics within an enterprise’s mission critical transactional data systems resulting (potentially, if we do it right) in a system that can analyse must faster. They say (as of 2017) about 10x faster than non-hybrid systems.