SAS is expanding its analytics integrations to multiple external data platforms, including Snowflake, Databricks, and Microsoft Fabric. With the new tools, Data Accelerator, SpeedyStore, and Intelligent Decisioning, SAS aims to bring models and compute closer to the data. Customer demand determines where the company will invest next.
Jared Peterson, Senior Vice President of Global Engineering at SAS, explains this in an interview with Techzine. For analytics pioneer SAS, it is crucial to bring its capabilities to the data environments where Viya platform users are located. Snowflake and Databricks have become the de facto standards in this area, while Microsoft Fabric is also rapidly gaining ground. The dominance of these three platforms means SAS is constantly evaluating how to integrate with other products.
In Peterson’s view, what SAS has done with its long-standing tech partner SingleStore is a good example of how integrations work. “It is really us taking SAS compute, pushing it into SingleStore, which is kind of the data platform sitting underneath that. The way that we kind of take the compute, the way we kind of drop it into a database, it’s essentially the same kind of approach architecturally when we move into other providers,” Peterson explains. The approach works both ways: bringing data to the SAS platform for modeling and bringing SAS Compute to the customer’s data location.
SpeedyStore: Rebranding and Further Development
One concrete manifestation of the strategy is SpeedyStore. The name is new, but the technology isn’t. SpeedyStore is a rebranding of the collaboration with SingleStore, the data platform that can run under the hood of the SAS environment. Peterson emphasizes that it is more than just a name change, because every month, they look at further integrating SAS functions into SingleStore.
As an example, he cites dashboards in SAS Visual Analytics. When a specific component of such a dashboard does not load quickly enough, SAS works with the customer and SingleStore to determine how to migrate that component. Step by step, more and more functionality is being brought to SingleStore. This will also yield benefits for other database integrations in the long term, according to Peterson.
SAS SpeedyStore, part of a major Viya update, runs as a cloud-native analytics platform alongside existing distributed data, without requiring data movement. This approach now forms the basis for further rollout to external platforms.
Databricks and Snowflake in the crosshairs
In mid-2025, SAS took another step beyond its own environment. In a May/June release, the company announced support for Databricks Spark. This allows SAS to run alongside that environment for the first time. It means, for example, that SAS models can be published directly into Databricks, enabling them to run faster on batch data. There is also close integration with Snowflake, using an alongside-database approach that follows the same architectural principles as SpeedyStore.
The reality is that many SAS users, often active in sensitive sectors, shape their data and AI strategies around these various platforms. They therefore often use Snowflake or Databricks tools alongside SAS Viya; in many cases, they even use all three. SAS must respond to this. Peterson makes it clear that customer demand is the driving force. Expansion follows where customers actually ask for it. This makes the approach dependent on the adoption signals SAS receives from its user base.
Decision Builder as a Fabric Application
Microsoft is a very important partner for SAS and is also visible as a main sponsor at every conference. Fabric has therefore become an important part of the collaboration. “Fabric is a big investment on their side. Not only just on the data fabric and data lakehouse kind of perspective, but they’re moving into analytics and compute and all those kind of things,” Peterson observes. Last year, SAS brought Decision Builder to Fabric, which combines multiple AI models, rules, and logic into a single workflow for decision-making.
Peterson also highlights the somewhat newer development, Intelligent Decisioning, a tool for automating and managing decisions. It relies on SAS’s business rules management, decision processing, real-time event detection, decision governance, and advanced analytics capabilities. “If you think about taking all the APIs and the architecture that sits underneath Intelligent Decisioning, we took that, and we dropped that on top of Fabric. But when you drop an application into Fabric, Microsoft brings along their own user interface standards and all those kinds of things,” explains Peterson. This way, it looks like a Fabric application, but it’s Intelligent Decisioning underneath the cover.
SAS is also using this application as a market signal. Intelligent Decisioning was an area Microsoft wasn’t planning to enter for the time being, making it a logical place for SAS to partner. As Decision Builder continues to gain adoption, SAS is considering bringing additional SAS functionality to Fabric.
With all these steps, SAS is ensuring that analytics gets closer to the data—that is, into the environments where customers work. This is necessary to take analytics to the next level, as companies are now being asked to leverage data insights more frequently and more quickly.