5 Reasons Your Data Lakehouse should Embrace Dremio Cloud

One — It’s Easy

Making the data lake the center of your data analytics up till recently has been a difficult proposition as many tools in the space require complex deployments and extensive configuration before you can even begin using the product. Dremio Cloud makes getting started with a data lakehouse as easy as signing up for email.

  • choose a name for your organization and initial project
  • connect your AWS account with a click of a button (Azure and GCP support to be added eventually)
  • done
  • Easily control compute scaling to limit costs but also to handle any level of concurrency
  • With Dremio Arctic catalogs, you can create and merge branches to isolate work on your data with an easy-to-use graphical UI.
  • The SQL Editor makes creating the right SQL queries easy with tools to assist in joins, lookup SQL functions, autocomplete, and more.

Two — Low Cost

The Dremio cloud platform’s standard tier is forever free, with no software or licensing costs. The only cost would be the cost of any AWS clusters that exist to execute your queries (an AWS expense, not a Dremio one). Still, with Dremio’s intuitive auto-scaling, clusters can be automatically created and scaled when there are workloads to execute and then automatically shut off where there is none, so no bills for unused compute create tremendous savings over other solutions.

Three — Fast

Dremio is not only easy and affordable but also blazing fast. At the core of Dremio’s performance are three technologies:

  • Creates a new standard for columnar data transport (Arrow Flight/Arrow Flight SQL) to reduce serialization/deserialization bottlenecks when transporting data between systems for huge performance benefits over ODBC/JDBC.
  • With Apache Arrow Gandiva common operations of arrow formatted data can be pre-compiled to binary for huge performance benefits

Four — Open

One of the things that leads to the high cost of data warehouses is the vendor lock-in, they know they can charge you more because its too hard to leave when your data is stored in proprietary formats. This lock-in also creates “lock-out” as your data may not be able to be used with other tools with other desirable features since it’s stuck in the data warehouse box.

  • You can query data in a variety of file formats like ORC, Parquet, JSON, CSV and more.
  • You can query data organized in many open table formats like Apache Iceberg and Delta Lake. (Here is a good article on what is a table format and the differences between different ones)
  • When using Dremio Arctic to catalog your data into Apache Iceberg tables, any engine that supports Nessie catalogs can connect and do operations on the data. (Arctic/Nessie catalogs enable branching and merging so you can isolate work on your data to avoid exposing partially updated data to your consumers)

Five — The Semantic Layer

Aside from querying your data, Dremio has several features that allow you to create a semantic layer over your data. By organizing your datasets into spaces and folders:

  • You can control the level of access they have (can they read, can they create reflections on the dataset, etc.)
  • You can create row and column policies to make sure only the right people can access sensitive data
  • Dremio becomes a key platform for implementing architectural patterns like Data Mesh (one more article on data mesh).
  • An easier place to manage regulatory compliance when it comes to data access


Dremio Cloud makes big data analytics easy, fast, affordable and open and provides a semantic layer that makes security and implementing a data mesh a breeze. With a free tier, there is very little reason not to make Dremio Cloud part of your data analytics toolbelt.



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Alex Merced Coder

Alex Merced Coder


Alex Merced is a Developer Advocate for Dremio and host of the Web Dev 101 and Datanation Podcasts.