Guide to Maintaining an Apache Iceberg Lakehouse
Data Lakehouse architecture has been the direction of data platform evolution over the last several years. By making your data platform more flexible, allowing…
Data Lakehouse architecture has been the direction of data platform evolution over the last several years. By making your data platform more flexible, allowing…
In optimizing our data infrastructure for cost-efficiency, ease of use, and business value, adopting new, valuable patterns can often be challenging due to…
Learn more about Apache Polaris by downloading a free early release copy of Apache Polaris: The Definitive Guide along with learning about Dremio’s Enterprise…
The Apache Iceberg project achieves a milestone with its 1.0 release — with its robust features and stable APIs, it’s never been a better time to adopt Iceberg as your data lakehouse table format.
Apache Iceberg Education Resources: Apache Iceberg Crash Course Webinar Series Free Copy of Apache Iceberg: The Definitive Guide Apache Iceberg 101 Blog…
Innovative data science, and the data volumes and varieties it requires, find a natural home in the data lake. But the latest generation of cloud-native data lakes also hosts a rising share of mainstream business intelligence (BI) projects.
Introduction The Data Lakehouse is rapidly emerging as the ideal data architecture, utilizing a single source of truth on your data lake.
Apache Iceberg is a data lakehouse table format revolutionizing the data industry with unique features such as advanced partitioning, ACID guarantees, schema…
In an ideal world, all our data would seamlessly flow into Apache Iceberg tables in our data lake, which would be perfectly organized and ready for analysis.
Moving data from source systems like Apache Druid to a dashboard traditionally involves a multi-step process: transferring data to a data lake, moving it into…