AtScale launched an expanded integration with Databricks that includes support for Databricks SQL and Unity Catalog as well as availability in Partner Connect.
Founded in 2013 and based in Boston, AtScale offers a semantic layer platform aimed at helping organizations easily organize and access their data to speed up the process of reaching insights that lead to business decisions.
Databricks, founded in 2013 and based in San Francisco, is a data lakehouse vendor whose platform combines the structured data storage capabilities of a data warehouse with the unstructured data storage capabilities of a data lake.
Over the past year, Databricks has been adding lakehouses specially geared toward certain industries to enable organizations in those industries to more easily get started using the vendor's platform. Among them, Databricks has launched lakehouses for financial services, healthcare, media and entertainment, and retail.
Databricks' Unity Catalog is a data catalog that enables organizations to put data governance and lineage measures in place. It was made generally available in June 2022.
Databricks SQL, meanwhile, is a serverless data warehouse that lets users run their SQL and analytics applications at high speed and scale. AtScale's availability on Partner Connect makes it easier for potential customers to discover AtScale and try a free version to see whether they want to deploy the platform.
Taken together, the new features are significant because they all simplify the combination of AtScale and Databricks, according to Donald Farmer, founder and principal at TreeHive Strategy.
"Being discoverable and readily accessible in these tools simply lowers the barrier for integration between Databricks and AtScale," he said. "And this does matter because integrating two sophisticated enterprise tools can be a daunting process. It's not so much that new capabilities are unleashed -- it's rather that the process is now more manageable and efficient."
Donald FarmerFounder and principal, TreeHive Strategy
Farmer added that AtScale's addition to Partner Connect is perhaps the most significant element of the expanded integration between AtScale and Databricks, given the exposure it will give AtScale among Databricks customers looking to expand their data and analytics capabilities.
Meanwhile, the vendors' capabilities complement one another, making them good partners with the integrations between the two additive for joint customers, Farmer continued.
He noted that lakehouses are attractive to organizations that use both structured and unstructured data to inform decisions. However, lakehouses don't necessarily enable users to describe the business semantics of their data.
"The partnership makes sense in both directions," Farmer said. "The AtScale semantic layer completes the picture by providing the right of kind of business-friendly data experience with a scale, performance and manageability that lives up to the promise of the data lakehouse. So, a good move all around."
Like many vendors, AtScale is wary of vendor lock-in and provides its users with choices. Therefore, although the expanded integration between AtScale and Databricks is significant for joint customers, AtScale has similar integrations with other data cloud vendors, according to Josh Epstein, AtScale's chief marketing officer.
In addition to Databricks, AtScale integrates with Amazon Redshift, Google BigQuery -- with AtScale available on Google Marketplace -- Microsoft Azure Synapse and Snowflake, he noted.
That said, the expanded integration between AtScale and Databricks is important for joint users, given its potential to foster both business intelligence and data science exploration on the same data and in the same location, Epstein continued.
"The ability to deliver business intelligence solutions based on the same data assets and on the same cloud data platform as AI, machine learning and data science opens the potential to bridge AI and BI data pipelines and workflows for a more integrated data program," he said.
Now that AtScale and Databricks have launched their expanded integration, the vendors are working to attract more customers to Databricks by offering them an alternative to traditional online analytical processing (OLAP) platforms that necessitate moving data between environments for analysis, according to Epstein.
OLAP enables users to extract data from data warehouses via OLAP cubes, which are cleansed data sets categorized by dimensions such as customers or geographic region. Those cubes can then be queried and analyzed before being returned to their data warehouse.
Databricks -- like Snowflake -- enables in-database analytics, eliminating the need to move data.
"AtScale and Databricks are leveraging these new integrations to ... create more seamless BI and analytics solutions for companies currently on Databricks or considering a move to Databricks," Epstein said. "In particular, there are many companies still relying on traditional OLAP solutions. AtScale and Databricks SQL does not require extracting data or managing large cube data structures."
Farmer noted that given its focus on semantic data modeling, AtScale has been able to differentiate itself from many of the other vendors that offer data management and analytics capabilities.
"AtScale [has] a mature, highly capable product that effectively solves one of the big problems in the modern stack, which is making sense of all the data that is available in its myriad forms," Farmer said. "For just this reason, there are lots of people talking about semantic layers now. AtScale has a head start in the maturity, integration and business-friendly experience of the product."
Eric Avidon is a senior news writer for TechTarget Editorial. He covers analytics and data management.