Data Lakehouse with Relational Junction
Simplify your data architecture by eliminating the data silos to effortlessly join analytics and data science.
Data Lakehouse Foundation
Eliminate Data Silos
Solve the challenges of traditional data lakes — get better data reliability, support for advanced analytics, and lower total cost of ownership.
Relational Junction Lakehouse Platform
Runs operations on one simplified architecture that avoids complex and redundant systems
Simplify ETL with improved reliability and cloud-scale production operations to help build the lakehouse foundation
Delivers massive scale and speed with optimized performance features such as indexing
Modern Data Lakehouse
Relational Junction enables data engineers, data scientists, and other data users to share data, collaborate more effectively, and deliver additional business insights.
Keep large volumes of diverse data in one place for advanced analytics and reporting
Eliminate redundancies that are possible if an organization uses a data lake and several data warehouses
Deploy in minutes to ensure your data team saves time and resources to focus on insights - just click and load!
Relational Junction’s Modern Data Lakehouse
Why Use a Data Lakehouse?
Benefits of a Data Lakehouse
Just like a data lake, a data lakehouse is built to house both structured and unstructured data. Businesses can work with unstructured data in one data repository rather than requiring both warehouse and lake infrastructure. Lakehouses are enabled by a new system design: implementing similar data structures and data management features to those in a data warehouse directly on top of low-cost cloud storage in open formats.
Data lakehouses enable structure and schema, like those used in a data warehouse, to be applied to the unstructured data of the type that would typically be stored in a data lake. This means that data users can access the information more quickly and start putting it to work. These data users might be data scientists or, increasingly, workers in any number of other roles that are seeing the benefits of augmenting themselves with analytics capabilities.
Enhancing Business Intelligence with a Data Lakehouse
The data lakehouse approach is one that’s likely to become increasingly popular as more organizations begin to understand the value of using unstructured data together with AI and machine learning. In the analytics journey, it’s a step up in maturity from combined data lake and data warehouse model. Until recently this has been seen as the only option for organizations that want to continue with legacy BI and analytics workflows, while also migrating towards smart, automated data initiatives.
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Data Lakehouse Resources
Do you have questions about building a data lakehouse? Learn why to use a data lakehouse, the benefits of analyzing data from multiple sources, & more!
RJ combines the best elements of data lakes and data warehouses — delivering performance with the low-cost, flexible object stores offered by data lakes.