Lentiq reimagines the vision of the data lake concept by moving away from a centralized, unified data repository to a fully distributed architecture. It aims to dramatically reduce friction between IT and the rest of the data teams.
Read about our company, how we work and the latest developments in the industry.
Lentiq reimagines the vision of the data lake concept by moving away from a centralized, unified data repository to a fully distributed architecture. It aims to dramatically reduce friction between IT and the rest of the data teams.
We envisioned a multi-cloud, production-scale data lake as a service that provides data teams the tools, the collaboration mechanisms, and the freedom they need to innovate. Now, it became a reality.
Unlike other services, we have a unique interconnected data pools architecture and a publish/subscribe data store concept that provides maximum technical flexibility inside one’s project while enforcing governance rules only when publishing data. Lentiq increases collaboration through data and knowledge sharing, thus offering a more agile development practice built around data projects.
We believe your data teams should be able to build use case-specific projects where they have the freedom to choose their technology stack, cloud provider, or region. By offering this flexibility and freedom, your data team will be more agile in choosing the right tools for the job and adapt to individual needs.
Data Pools – the next generation Data Lake
When designing the Lentiq architecture, we understood that a traditional data lake is difficult to use for various use cases at the same time by different departments within the same company. It is simply rigid. We had to innovate. We had to rethink the way data lakes are built from the core. So, the concept of data pools was born.
Data pools are, in fact, micro-data lakes. They provide everything a data science team needs: data management capabilities, notebook environments, Apache Spark cluster management, and others.
Each data pool works independently, has its own budget and resources, while at the same time it is seamlessly interconnected to other data pools within the same company, even if ran on different cloud providers. A data pool packs the best tools needed for each specific business use case, and with the noHadoop technology behind it, teams are closer to the data source. Teams are agile and free to work on their projects instantly.
Guiding principles
Lentiq’s goal is to allow as many users as possible inside an organization to access data and to offer the environment where one can perform analytics and machine learning in a friendly manner. We strongly believe transformative innovation can only be achieved through a human-centric machine learning approach for all data projects.
There are a few key features that help us achieve our vision
Our goal is to offer a product that can quickly adapt to individual data teams needs and become a platform that enables innovation. We pride on some additional features: data and metadata management, application management, notebook sharing, data sharing, infrastructure, and budget management.
At Lentiq, we build products for real users, and this is just the starting point. We have a well-defined roadmap that we plan to deliver with consistent velocity. We are going to bring in more features and adapt the product, as input from the community, data scientists, data engineers, business analysts, and other users start to come in.
In the upcoming months, we are going to keep you constantly updated with our progress, and we want to involve you in evolving this product. It is going to be an exciting year for Lentiq EdgeLake, and all your feedback/questions/suggestions are much appreciated.
Feel free to drop us a few words at hello@lentiq.com.