Migrate from Hadoop

Move your legacy Hadoop platform to the Databricks Lakehouse

Hadoop has proven unscalable, overly complex and unable to deliver on innovative use cases. Migrating from Hadoop to Databricks will help you scale effectively, simplify your data platform and accelerate innovation with support for analytics, machine learning and AI.

“Moving from Hadoop to Databricks has unlocked significant business value. We are able to process more data faster, build reliable ETL pipelines, and make it easier for our analysts to build models that deliver the viewing experiences our customers want.”

— Parijat Dey, Assistant Vice President, Digital Transformation and Technology, Viacom18

“There’s more data running in real time but with no increase in costs vs. EMR. Like for like, it works out as a 60% cost improvement.”

— Eoin O’Flanagan, Head of Data Engineering, Gousto

The challenge with Hadoop

On-premises Hadoop deployments have significant limitations, including wasted hardware capacity, high DevOps burden, increased power costs and software version upgrades.

Even if you migrate legacy on-premises Hadoop workloads to cloud-based managed services like EMR, HDInsight or Dataproc, you’ll still run into the same reliability and scalability issues. This leads to a lot of time being wasted on troubleshooting, infrastructure, resource management overhead and stitching different managed services on the cloud to maintain an end-to-end pipeline.

To learn more about the challenges organizations face with on-premises as well as cloud deployments of Hadoop, check out these blogs:

Blog

It’s Time to Re-evaluate Your Relationship With Hadoop

7 Reasons to Migrate From Your Cloud-Based Hadoop

Simplify your data platform

Get a single modern platform for all your data, analytics and AI use cases. Unify governance and the user experience across clouds and data teams.

Scale cost-effectively

Stop managing servers, and scale on demand with serverless. Run data warehousing at scale with up to 12x better price/performance.

Accelerate innovation

Build AI, ML and real-time analytics capabilities faster with collaborative, self-service tools and open source technologies such as MLflow and Apache Spark™.