On the Integration of SAS® Viya® with SingleStore. Q&A with Kyle Basile

  1. SAS has joined forces with SingleStore to help organizations “remove barriers to data access, maximize performance and scalability, and uncover key data-driven insights”. How do you plan to integrate SAS® Viya® with SingleStore? 

We have integrated SAS Viya’s world class analytical capabilities with SingleStore’s horizontal scaling and parallel processing to provide an industry leading analytic data framework.  Analytic workloads can now leverage any level of compute, whether on-prem or in the cloud, to optimize both performance and cost. The key insights formulated within SAS Viya are now more accessible and performant than any analytic solution on the market.

  • What are the advantages for a customer in using SAS analytics and AI technology on data stored in SingleStore’s cloud-native real-time database?

SAS Viya with SingleStore tightly couples Viya AI/ML models with SingleStore’s scalable real-time database. With a modern elastic approach to both analytical and data engines we can dramatically reduce the technical debt through reducing duplication, enhanced compression, and cheaper hardware.  We can also expect enhance performance through minimizing data movement and optimizing available compute.

  • Can you give us some examples of the kind of mission critical applications that will benefit from this combined technology?

Mission critical analytics such as risk, fraud, etc. will not only become more performant and cost effective but now easily be accessible in a real-time relational database.  Other downstream applications that are dependent on the results of these analytical models will get data faster with minimal data movement. SAS Viya with SingleStore delvers capabilities that simplify and accelerate the iterative data and analytic processes to improve speed-to-decision and unlock critical value.

  • You mentioned in your press release that “the integration provides flexible, open access to curated data to help accelerate value for cloud, hybrid and on-premises deployments.” What does it mean in practice?

Historically, data analysts and data scientists have had to extract, transform, and load data from less performant data storage.  They also had to leverage these less performant data infrastructures to scale out on big data. The SAS Viya with SingleStore product becomes the single source of truth for analytical data as well as an easily scalable solution for big data analytics. The integration between SAS and SingleStore lets customers prepare, model, and store their data directly in SingleStore. It enables them to run SAS analytics directly against high-scale data in SingleStore, avoiding costly, time-consuming data movement.

  • The integration of SAS Viya with SingleStore enables the advanced AI and machine learning analytics of SAS to be executed directly against relational database tables in SingleStore. What is the rationale behind this architectural choice?

Organizations need quick answers to critical questions to make informed decisions. How? The analytics life cycle is the tried-and-true way to deliver fast insights. It’s a continuous process of managing data and developing and deploying models. Businesses can accelerate their analytics journey by simplifying the underlying data platform architecture and automating the end-to-end data pipeline. Unfortunately, many organizations fail to do this effectively.

With SingleStore’s real-time distributed SQL database and SAS’ analytics performance, this integration delivers key advantages to support a modern cloud architecture.  SAS users now have the ability to run performant and cost-effective big data analytics due to the reduction in data movement and in database capabilities.  There are also engineered embedded processes within SingleStore that SAS code can leverage in order to enhance push down analytics.

  • Is it going to reduce duplicative data stores? 

Yes, SAS and SingleStore will considerably reduce customers’ technical debt of duplicative data stores, helping improve analytic workload performance and ultimately uncover key competitive advantages. A common practice by many data scientists is to create their own silo’d data store due to the nature of existing infrastructures.  With the scalability and open nature of SingleStore, users have less need to extract data as they can perform data prep, data curation, model development directly on the data in SingleStore. This solution promotes a healthy analytic data environment that enhances the user experience.

  • What about improved performance? Can you give us an estimate on this?

When embedded into SAS® Viya®, SingleStore eliminates data movement complexities while expediting analytics processing. That means you can store data in our high-performance, secure SingleStore database for easy access and deploy it your way — whether that’s on-premises, or in a hybrid or public cloud. This includes:

  • Accelerating time-to-decisions – Get faster time-to-insights with quicker ingest to process and analyze data anywhere, in real time.
  • Lowering TCO – Reduce costs of analytic decisions through efficient data storage and eliminate redundancies.
  • Reducing complexities – Simplify data access and improve productivity by better managing data at scale.

An easy example of enhanced performance is around data ingest.  If we imagine a large file/table with customer 360 data and all transactions.  We want to run a correlation model against that large table.  SingleStore provides a feature that allows users to run the correlation model without pulling large amounts into memory or the engine.  The platform is also parallelizing workloads across the distributed system optimizing analytical workloads.


Kyle Basile, Director of Partner Sales, SingleStore

Kyle Basile is the Director of Partner Sales for SingleStore. He focuses on providing agile, high-ROI solutions to customers across the broadest range of enterprise, cloud, big data, and unstructured data sources.

Kyle teams directly with enterprise customer executives and key senior leaders. He is responsible for revenue generation, sales play innovation, opportunity management, customer relationships, and high customer satisfaction.

Kyle has a BS degree in Electrical and Computer Engineering along with more than 10 years of experience in the Software industry across analytics, data integration, and data management.

Sponsored by SingleStore.

You may also like...