Is your organization struggling with existing Hadoop environments that are costly, complex to manage and maintain, and limited in scale and performance?
Dremio’s Hadoop Modernization offer improves performance, reduces costs, and delivers unified self-service analytics.
Dremio:
Modernizes the query engine with Dremio and provides self-service.
Rapidly and easily migrates Hadoop data to on-premise object storage.
Enables users to create an open, scalable, and highly-manageable data lakehouse.
In the initial phase, we deploy Dremio, which delivers immediate improvement in performance. Dremio’s data lake engine, leveraging high performing in-memory execution, and predictive pipelining. Reflections, our innovative query acceleration technology, delivers unmatched performance directly on data lake storage.
Dremio’s semantic layer empowers users to seamlessly access and query data from both legacy Hadoop environments and new object stores, even as the migration process is underway. Dremio provides self service by unifying data sources, rapidly creating data products for each domain, and ensuring governance across entire data architectures.
In the final phase, we optimize the new environment, transforming it into a modern data lake house. This optimization leverages the latest innovations in open source standards, enhancing data management and analytics capabilities. For example, using Apache Iceberg tables greatly improves the management, organization, and tracking of all of the files that make up tables in your new lakehouse.
From Hadoop to Data Lakehouse: A Migration Playbook
Getting Started with Hadoop Modernization
How to Modernize Hive to the Data Lakehouse with Dremio and Apache Iceberg
How NetApp is Redefining the Customer Experience with Product Analytics
NCR Uses Dremio to Deliver Business Insights at a Faster Clip
TransUnion- Making Data Customers More Efficient
Getting Started with Dremio’s Data Lakehouse