Snowflake is continuing to grow the capabilities of its cloud architecture with new developer and security capabilities that aim to help users optimize information.
In the wake of its blockbuster IPO, cloud data warehouse services vendor Snowflake is growing its data cloud offering with the Snowpark feature, a set of new services and capabilities to improve developer experience.
The Snowflake update also improves unstructured data support and security.
Snowflake, based in San Mateo, Calif., went public on Sept. 16 in one of the largest software initial public offerings ever, raising about $4 billion and bringing the eight-year-old company's valuation to about $33 billion.
Over the course of 2020, the company has been adding capabilities to its data cloud platform that aim to make it easier for users to connect and use more sources of data.
At Snowflake's Data Cloud Summit 2020 virtual conference on Nov. 17, the vendor introduced a series of enhanced capabilities that continues to build on the theme of enabling more access to more data. The new capabilities are now available in limited previews, with full general availability expected in early 2021.
"Our recent listing on the New York Stock Exchange was billed as the largest software IPO in history, but the Data Cloud conversation is bigger," Snowflake CEO Frank Slootman said during the opening keynote.
Among Snowflake's users is New York City-based S&P Global, which provides data services to organizations around the world across its multiple divisions.
Warren Breakstone, managing director and chief product officer at S&P Global
In a press and analyst briefing on Nov. 16 ahead of the Snowflake event, Warren Breakstone, managing director and chief product officer at S&P Global, talked about the new features that he said will help his company and its users.
Our clients are always looking to be able to get more out of the data, so the focus on the query acceleration really sort of hits the bull's eye.
Warren BreakstoneManaging Director and Chief Product Officer, S&P Global
Among the enhanced tools that Breakstone said he's interested in is a new query acceleration capability as well as updated search optimization.
The new Query Acceleration Service is a technology Snowflake built to reduce query runtimes against large data sets. Similarly, the Search Optimization Service is for improving performance in data searches.
"Our clients are always looking to be able to get more out of the data, so the focus on the query acceleration really sort of hits the bull's eye," Breakstone said.
Breakstone added that a key challenge facing many of S&P's clients is dealing with an overwhelming amount of data, which often makes it hard for them to find the data they are looking for. So the ability to helps users find what they're searching for faster is powerful, he said.
Taking the Snowflake Data Cloud to the Snowpark
Building out data pipelines to interact with data within the Snowflake Data Cloud is getting a boost with the new Snowpark service.
Christian Kleinerman, senior vice president of product at Snowflake, said Snowpark provides a new way for users to program data in Snowflake. The promise of Snowpark, according to Kleinerman, is that users can now take any data workload they want and use the code they need to prepare and use the data.
Snowpark provides new programming language support, including Java, Scala and Python, natively into Snowflake. Also, Snowpark brings a set of optimized APIs that enables users to program data in Snowflake that is optimized for running against the core Snowflake engine.
Complementing the Snowpark service is new support for serverless tasks in the Snowflake Data Cloud.
Serverless is an approach also sometimes referred to as event-driven computing in which a given function only executes when needed, instead of requiring an always-on compute instance in the cloud. With serverless tasks, users can schedule a given data preparation or transformation activity, in a more optimized approach.
Snowflake security improvements
At Snowflake's virtual event in June, #SayHelloToTheDataCloud, the vendor unveiled a dynamic data masking feature that improves improve security by reducing access to certain data. Now Snowflake is completing dynamic data masking with a row-based access policy for data.
"Now you can conditionally display or hide a row depending on who is querying," Kleinerman said. "The combination of dynamic data masking and row-based policies provides a very powerful and fine-grained access control all dynamically informed by Snowflake at query run time."
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