Graphenus is a Big Data distribution, which manages and controls end-to-end the data lifecycle: from infrastructure management and monitoring to data storage, analysis and governance.
Graphenus has a multitude of out-of-the-box functionality, facilitating the implementation of different use cases, including analytics and ML.
Graphenus integrates and secures opensource tools
and analytical data processing and data analytics
Graphenus allows you to add/remove components by means of mechanisms
plug&play
Graphenus is
fully-containerised, allowing scalability of services according to different needs
Our distribution is born with a clear purpose: to provide maximum security and flexibility to respond to specific business needs.
Aspects
Graphenus is a multi-purpose, open, flexible, scalable and secure data platform that facilitates analytics and data governance across the organisation.
differentials
Graphenus is a multi-purpose, open, flexible, scalable and secure data platform that facilitates analytics and data governance across the organisation.
Aspects
differentials
Security
Security
Graphenus has an aggressive but flexible evolutionary roadmap, able to prioritise the specific needs of a particular customer.
Competitiveness
Competitiveness
We believe that, until now, the lack of choice has resulted in a market that is not very competitive, with much room for improvement.
Access to different data sources, including in real time.
TRINO | SPARK | KAFKA
High-availability distributed storage.
HDFS
Container management.
DOCKER SWARM
Distributed batch and streaming data processing.
YARN | SPARK
Process planner
AIRFLOW
Data representation and SQL queries.
HIVE | TRINO
Build notebooks for computing, data science or machine learning.
JUPYTER NOTEBOOKS
User interface for interacting with the tools of the distro.
HUE
Monitoring of the use and operation of all services.
CADVISOR , LOKI , PROMETHEUS , GRAFANA
Identification, authentication and authorisation of users.
FREEIPA | KERBEROS | KNOX | KEYCLOAK | RANGER | RANGER
Data governance throughout the information processing cycle
Linkedin DataHub
