Doing More with Less in the Cloud with Databricks and Rivery

Modern business is dependent on a balance between innovation and costs—and the world of data is no different. While data teams must adapt to the rigid business demands of speed and reliability—as well as the ability to support GenAI initiatives through complex integrations—they must simultaneously keep expenditure low.

Pavithra Rao, delivery solutions architect at Databricks, and Taylor McGrath, VP solutions engineering at Rivery, joined DBTA’s webinar, From Bottlenecks to Breakthroughs: Data Integration Unleashed, to examine how enterprises can put advanced cloud computing to work—and accelerate their data delivery by 7.5X—while maintaining cost efficiency.

Rao asserted that the winners in every industry will be data and AI companies. Meaning, those who “make most effective use of data and AI” will be competitive forces in the years to come.

However, this is easier said than done, pointed out Rao, as most organizations struggle to adopt and manage the various intricacies of data management—from data lakes to data science, governance, orchestration and ETL, machine learning, BI, and more. This is due to three key reasons:

  1. Data and AI are siloed.
  2. Data privacy and control are challenges.
  3. Data management is dependent on highly technical staff.

Databricks pioneered the lakehouse architecture in 2020, where today, 74% of global enterprises have adopted a lakehouse, according to MIT Technology Review Insights, 2023. Rao argued that a data lakehouse—which acts as an open, unified foundation for enterprise data—and GenAI combine to form a data intelligence platform that helps to democratize data and AI across your entire organization.

Databricks’ Data Intelligence Platform “opens up a whole world of possibilities,” said Rao, unifying data and governance. The platform utilizes an AI-powered intelligence engine to understand the semantics of your data, persisting that understanding across the platform.

Ultimately, Databricks’ Data Intelligence Platform offers a variety of benefits that empower a data-driven organization, including:

  • Rapid, accessible insights interfaced with natural language
  • Removal of data complexity through AI
  • Train and serve custom GenAI apps on proprietary data while maintaining privacy
  • Easy integration with the entire data and AI ecosystem

Enterprises want time-to-value while enabling personas with different skillsets the ability to access that data, according to McGrath. Yet, these problems are complex, and many point solutions on the market today only solve one or two simple problems.

Stitching together too many platforms for data integration results in:

  • Data silos
  • Inconsistent governance
  • Data breakage and reduced reliability
  • Slowed productivity due to context switching

To solve this problem, Rivery delivers a Modern Data Integration Platform that places ease at the forefront, offering the simplicity of a low-code solution with the adaptability of custom code, the scalability of managed SaaS, and the cost efficiency of pay-per-use.

Rivery aims to “provide an easy-to-use platform that can solve…needs across an end-to-end ELT use case, whether that’s simple or complex,” said McGrath.

The Rivery Modern Data Integration Platform helps to declutter data integration sprawl with a minimalistic set of building blocks, allowing enterprises to connect to any data source while maintaining a unified architecture. The platform also allows enterprises to:

  • Run multi-step, SQL-based transformations directly inside your cloud data warehouse
  • Prepare, clean, and convert raw data into structured data
  • Automate the entire data integration process, including data transformation via Rivery’s Logic Rivers
  • Configure data pipelines per business unit without creating a data team bottleneck
  • Separate walled-off environments for each stage of development
  • Easily control deployment from one environment to another, with built-in dependencies, environment variables, and groups
  • Revert changes with built-in version control
  • Remotely execute, edit, deploy, and manage data pipelines via a command-line interface (CLI) or API

For the full discussion of leveraging advanced cloud computing while managing costs, you can view an archived version of the webinar here.