The Graphenus information processing layer is based on Sparkthe engine distributed computing The most modern and most widely used today. In addition to Spark, Graphenus is making massive use of the ecosystem HadoopThe most widespread project for the development of projects that require scalability and distributed computing.
- High-availability, fault-tolerant storage.
- Compatibility with other storage systems and formats.
- Cost efficient and highly scalable.
Distributed execution of fault-tolerant applications.
Definition of resource queues for users (basic functionality for multitenant).
- Spark is the reference framework for processing large amounts of data in a distributed manner and with high performance thanks to in-memory processing.
Spark and Hadoop are at the heart of Graphenus, unifying the information processing processes within the platform.
Full scalability of storage and processes The data processing is transparent and without the need to re-code applications.
Use and development of machine learning algorithms using different programming languages and libraries.
Simple and highly efficient analytics using SQL on the various datasets.
Reuse of the same business logic in batch and streaming processes.
Out-of-the-box compatibility with multiple data science, machine learning and business intelligence tools and libraries.
