Splice Machine is a revolutionary database management system that makes it easier for data scientists to connect dots in both the data center and cloud. It’s the only SQL scale-out relational database management system with built-in native machine learning. In a nutshell, Splice Machine does the grunge work so you don’t have to.
In this eSPEAKS video, we cover:
- The type of work Splice Machine does
- A demonstration of how easy and simple the application is to use
- Use cases of the app
For an insider’s scoop, Chris spoke with:
Monte Zweben, co-founder and CEO, Splice Machine; Host: Chris Preimesberger, Editor, eWEEK
San Francisco-based startup Splice Machine, whose database management system is specifically optimized for hybrid clouds, has announced the availability of its automated application platform on the Microsoft Azure cloud service.
Splice Machine’s Online Predictive Processing Platform (OLPP) is designed to power new-generation predictive analytics applications that run both on premises and in the cloud—or multiple clouds—as needed in production requirements.
Becoming available on the growing Microsoft Azure cloud service gives admins another way to use the data platform while having the independence to deploy on premises, on Amazon Web Services, Azure, or both, the company said.
Using Splice Machine, the company claims, enterprises can develop and deploy smarter predictive applications that integrate integrate fast data streaming, transactional workloads, analytics and machine learning, enabling business transformation at performance and scale.
Using Splice Machine’s cloud service replaces or offloads traditional and cloud-based RDBMS and cloud-based or on-premises data warehouse packages. It can be used on premises with Hadoop clusters, but it masks the complexity of operating those Hadoop analytics deployments, since it handles all the data movement automatically.
Unlike most data platforms, Splice Machine is a scale-out SQL data platform that can run fast OLTP