Perform machine learning and analytics at scale, do data and metadata management in a multi-cloud, production-scale data lake as a service. Offer the maximum technical flexibility to your data teams, while also ensuring data governance at the data lake level. Provision live, in less than 10 minutes, in one or multiple clouds. Start experimenting with data now.
We believe that to be successful, a data team must be as free as possible from the restraints of centralized governance and standardization. With that in mind, we created a platform that moves away from a centralized, unified data repository to a fully distributed architecture made of interconnected data pools: Lentiq EdgeLake.
Our publish/subscribe data store concept provides maximum technical freedom within one's project, while enforcing governance rules only when publishing data.
A data pool is a micro-data lake. It provides everything a data scientist or data engineer needs: data management capabilities, notebook environments, apache spark cluster management, and others.
Data Pools are designed to operate independently and can even run on different cloud vendors. Only when sharing data with other data pools, the governance rules are enforced.
This design allows data teams to leverage the best tools and skillsets available for the job, mitigate local infrastructure requirements and apply governance policies without hindering innovation and adaptability.