What is lakeFS? As data practitioners, we use many different terms to talk about what we do – we call it business intelligence, analytics, data pipelines, or insights. But there’s one term that captures what we do really well: delivering products. When we were leading a large R&D organization, we couldn’t help but wonder about …
lakeFS Cloud provides a Git-like repository for data lakes in a hosted version available in AWS Marketplace NEW YORK and TEL AVIV, June 22, 2022–lakeFS, the technology that brings streamlined data lifecycle management and version control to data lakes, is announcing lakeFS Cloud, a fully managed SaaS version of its open-source technology. The new hosted …
LakeFS Introduces a New Approach to Data Manageability and Reliability Read More »
A year has passed since we shared the State of Data Engineering 2021. And since we released that article last May, not much has changed in the data landscape. In fact, we had discussions internally about whether we should even do an update for 2022. We kid. It was another year worthy of its own …
As organizations develop new product offerings and data streams, data engineers deal with the largest and most complex datasets ever. Add growing teams and new data orchestration tools into the mix, and you got yourself a pretty complicated data landscape. As the global cloud storage market grows, so does the complexity of managing data. This …
Gain the confidence to mess with your datawithout making a mess of your data. “If it hurts, do it more often.” is a wise piece of advice that DevOps engineers often repeat. Unless you are a masochist, following this advice will naturally lead you to finding ways to make the process being repeated less painful. …
The last decade saw an unprecedented rise in the number of organizations that base their decisions and operations on data. The number of digital products that collect and process data and use it to fuel decision-making algorithms for enhancing future services is also growing at a very fast pace. That’s why data and data quality …
Clearing the mess – How to ensure data quality with versioning Read More »
Modern data engineering practices lead more and more organizations to a broader use of object stores. This happens due to the rising scale and complexity of the data that they manage – along with the growing variety of use cases that these data warehouses need to cater: from machine learning and algorithm development, to analytics …
5 Painful mistakes data engineers make, and how to avoid them Read More »
Introduction It may seem strange at first, but increasingly we cannot be sure when putting or getting data from an object store that the data is being sent around is coming from the service we think it is. Imitation is the highest form of flattery, and given cloud object storages’ popularity, they have naturally attracted …
What if you could manage your data lake just like you manage code? With rollback, versioning, and branching capabilities on top of your existing data lake? lakeFS is an open-source project that provides a Git-like version control interface for data lakes, with seamless integration to most data tools and frameworks. lakeFS enables you to easily …
The lakeFS playground is now live and everybody can play! Read More »
As data practitioners, we use many different terms to talk about what we do – we call it business intelligence, analytics, data pipelines, or insights. But there’s one term that captures what we do really well: delivering products. When I was leading a 200 person engineering team at SimilarWeb, I couldn’t help but notice about …
Closing the Gap: Lifecycle Management for Data Products Read More »
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