
GNARLY DATA WAVES EPISODE
Overview of Dremio’s Data Lakehouse
On our 1st episode of Gnarly Data Waves, Read Maloney provides an Overview of Getting Started with Dremio's Data Lakehouse and showcase Dremio Use Cases advantages.
Watch now (27 min)Self-service analytics with data warehouse functionality and data lake flexibility across all your data
1 min
Survey Report
Gain unprecedented insights into the evolving landscape of data lakehouses and benchmark your organization with Dremio's State of the Data Lakehouse Survey Report. This survey of 500 full-time IT and data professionals from large enterprises offers fresh insights on data lakehouse trends, adoption and associated benefits.
Unified data access, modern and intuitive U/I, semantic layer, and built for SQL.
Based on community-driven standards, including Apache Arrow, Apache Iceberg and Apache Parquet.
Lightning-fast queries, high concurrency, and no expensive data copies to manage.
A SQL query engine with a built-in semantic layer and intuitive user interface. With Dremio Sonar, organizations can quickly access the data they need, query across data sources, create views, and update Apache Iceberg tables with data manipulation language (DML).
Check Out Dremio Sonar Query Engine6 min
A data lakehouse management service that enables data teams to manage data-as-code with Git-like operations, optimizes tables automatically, and provides a data catalog. Dremio Arctic makes it easier for data teams to provide improved governance, data quality, and query performance. With Dremio Arctic, data teams can select their query engine of choice.
Check Out Dremio ArcticProvide self-service to the business by unifying data sources, rapidly creating data products for each domain, and ensuring governance across the entire architecture.
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Move from HDFS to cloud object storage, such as Amazon S3, and replace Hive, Impala and other legacy query engines with Dremio to turn your data lake into a high performance data lakehouse.
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Departments such as marketing, trading, and supply chain require high scale, high performance, and self-service for the business. Dremio’s open data lakehouse is the ideal fit for data driven departments.
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In many architectures, data ingested into a data lake is then copied into a database or data warehouse to provide improved performance as well as security and governance controls. With Dremio’s data lakehouse, customers can remove these systems and deliver governance and high performance, directly on the data lake.
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Dremio’s performance allows engineers to treat their data lake + Dremio as a database for analytical applications and application components. Engineers can use Apache Superset for customer dashboards or other development tools to build directly on top of Dremio.
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Dremio partners with hundreds of leading data storage, BI tool, and ETL vendors to provide a comprehensive set of functionality for organizations of any size.
Dremio helps organizations become more data driven with self-service analytics and more efficient by offloading use cases from expensive and proprietary data warehouses to our open data lakehouse. Dremio exceeds the performance and scale requirements of the most demanding and largest enterprises in the world, including 5 of the Fortune 10.
On our 1st episode of Gnarly Data Waves, Read Maloney provides an Overview of Getting Started with Dremio's Data Lakehouse and showcase Dremio Use Cases advantages.
Watch now (27 min)A data lakehouse uses SQL commands to query cloud data lake storage, simplifying data access and governance for both BI and data science.
Learn moreOpen data lakehouse architectures speed insights and deliver self-service analytics capabilities.
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