Data fuels the modern enterprise — today more than ever, businesses compete on their ability to turn big data into essential business insights. Increasingly, enterprises leverage data lakes as the platform used to store data for analytical purposes, combined with various compute engines for processing that data.
A data lake consists of a cost-effective and scalable storage system along with one or more compute engines. It supports a broad range of essential functions from traditional decision support to business analytics to data science.Learn more about data lake solutions and how they can help your business be more productive and efficient.Learn About Data Lakes
Explore this interactive demo and see how Dremio's Intelligent Lakehouse enables Agentic AI
Traditionally, enterprises have relied on data warehouses to manage data for operational reporting, business intelligence and a variety of essential decision support applications. However, data lakes implemented in a loosely coupled cloud architecture have numerous benefits over tightly coupled data warehouses.
Learn about the key differences between data lakes and data warehouses and discover how new technological approaches can help you modernize your data architecture and realize better performance and flexibility at a fraction of the cost.
While traditional legacy data lakes have been built on on-premises Hadoop clusters, many enterprises are 
modernizing their data lakes by migrating them to the cloud as an infrastructure-as-a-service.
A cloud data lake is a cloud-hosted centralized repository that allows you to store all your structured and unstructured data at any scale, typically using an object store. The two most common cloud data lake object stores are:
A data lake engine is an application or service which queries and/or processes the vast sets of data stored in a data lake. Rather than relying on expensive, complex and proprietary data warehouse environments, a data lake engine supports both data science and business intelligence queries directly on the data lake.
For any business using data warehouses and data lakes, or for businesses simply wanting to get more capability from their data lake, the data lake engine is a game changer.
Deploy agentic analytics directly on Apache Iceberg data with no pipelines and no added overhead.
By unifying data from diverse sources, simplifying data operations, and providing powerful tools for data management, Dremio stands out as a comprehensive solution for modern data needs. Whether you are a data engineer, business analyst, or data scientist, harnessing the combined power of Dremio and Apache Iceberg will undoubtedly be a valuable asset in your data management toolkit.
We're always looking for ways to better handle and save money on our data. That's why the "data lakehouse" is becoming so popular. It offers a mix of the flexibility of data lakes and the ease of use and performance of data warehouses. The goal? Make data handling easier and cheaper. So, how do we […]
This blog helps you learn about table-driven access policies in Dremio Cloud and Dremio Software v24.1+.
