Microsoft's latest cloud data warehouse release retains its decoupled compute-storage advantage, while crafting parity with Amazon Redshift's local storage performance.

In the ongoing debate about where companies ought to store data they want to analyze – in a data warehouses or in data lake — Databricks today unveiled a third way. With SQL Analytics, Databricks is ...

Microsoft's drive to put Azure SQL Data Warehouse on more equal footing with SQL Server is finally paying off.

Fresh from last week's Build developer conference in San Francisco, Microsoft executives appeared at the company's first-ever Ignite conference in Chicago and provided more details about the company's ...

SQL Analytics realizes Databricks' vision for a lakehouse architecture that combines data warehousing performance with data lake economics, resulting in up to 9x better price/performance than ...

Azure SQL Data Warehouse was built on a similar elastic massively parallel processing (MPP) architecture that is found in its SQL Server 2016 database to provide column stores for storage ...

There once was no alternative to building a data warehouse on-premise, but with cloud providers targeting analytics, building data warehouses on-site is looking obsolete.

Data lakehouse architecture combines the best of cloud data lake and warehousing architectures to give teams the most recent data.

Architecture Data Vault 2.0 Architecture is based on three-tier data warehouse architecture. The tiers are commonly identified as staging or landing zone, data warehouse, and information delivery ...

With modern data hub you can deploy a solution in a matter of days or weeks, Carr said. Traditional approaches incur several problems including cost, planning, and capturing data at the right times.