February brought a number of exciting enhancements, especially for customers building and running data pipelines in Snowflake, including support for Snowpark stored procedures and flexible task execution. Additionally, customers get improved impact analysis through support for object dependencies, and we continue to expand Snowflake’s global reach with the regional availability of UAE North (Dubai) on Azure. Read on for more!
Data Programmability and Pipelines
Operationalizing data pipelines with Snowpark
With Snowpark’s new stored procedures (for Scala) capabilities, users can now host Snowpark pipelines right inside Snowflake—using a Snowflake virtual warehouse as the compute framework and natively integrating with Snowflake features like Tasks for scheduling. This feature simplifies the end-to-end story by reducing the number of systems involved and by keeping everything self-contained in Snowflake. Read more about Snowpark stored procedures, now available in preview to all customers on all three cloud platforms.
Java table functions now in GA
Table functions are now generally available on AWS. Previously, Snowflake only supported scalar functions—ones that operate on each row in isolation, producing a single (possibly complex) result. Scalar functions are nice. They’re simple to write, they’re simple for Snowflake to scale out as part of a query, and they address a broad range of problems. But there are things you can’t do with scalar functions. This includes returning multiple rows for each input row, maintaining state across multiple rows, and returning a single result for a group of rows. However, all of these things are possible with table functions. To learn more about how Snowflake’s user-defined table functions work, start here.
Direct execution of tasks
With this release, users now have the option to manually execute a single run of a scheduled task (i.e., a standalone task or root task in a task tree). Executing a run of a root task triggers a cascading run of child tasks in the tree, as though the root task had run on its defined schedule. Previously, a scheduled task could only start when its next scheduled run occurred. Learn more about this new manual capability, now in preview.
Object dependencies for impact analysis
With this release, Snowflake is pleased to announce support for object dependencies in public preview. Object dependencies is an Account Usage view that helps data teams identify which objects depend on others, such as tables backing a view. With this new level of visibility, you can proactively assess potential downstream impacts of modifying objects so you can push changes with confidence. To learn more about this, check out this video from our recent Snowday event.
New region alert: UAE North (Dubai) on Azure
Snowflake is expanding its availability to the United Arab Emirates North (Dubai) region on Azure. With this expansion, Snowflake now supports 30 global regions across three cloud platforms (AWS, GCP, and Azure)—including three regions for compliance with U.S. government regulations. See our full list of supported regions here.
Search Optimization Service cost estimate function updated
The cost estimate function for Search Optimization Service will change to use a small sample of the table as the basis for estimating costs, and therefore will require a warehouse to run. This update significantly improves estimates for the build and maintenance costs of using the Search Optimization Service. Visit our documentation page to read more about managing costs for this service.
Snowflake works with a wide array of industry-leading tools and technologies. This integration helps customers access the platform through an extensive ecosystem of connectors, drivers, programming languages, and tools. With this current release, Snowflake announced improved support for its SQL API including support for concurrent fetches.
Snowflake Data Marketplace
Snowflake customers can tap into Snowflake Data Marketplace to discover and access helpful third-party data and services from more than 200 providers (as of October 1, 2021) as well as market their own products across the Snowflake Data Cloud. Visit Snowflake Data Marketplace.
Recently added Snowflake Data Marketplace Providers
Treasury & Equities Market Data
DTCC is the premier post-trade market infrastructure for the global financial services industry. From 21 locations around the world, DTCC automates, centralizes, and standardizes the processing of financial transactions—mitigating risk, increasing transparency, and driving efficiency for thousands of broker/dealers, custodian banks, and asset managers. Industry owned and governed, the firm simplifies the complexities of clearing, settlement, asset servicing, data management, data reporting, and information services across asset classes. Learn more.
Hedge Fund Research
Established in 1992, HFR has innovated indices across the spectrum of hedge fund strategies and regions. HFR has become the chosen single source of hedge fund information and analysis used by firms of all sizes. HFR databases have been in operation for over 20 years and they cover the most important years of the industry’s development to date. Access detailed profiles of hedge funds, funds of funds, managed futures, and liquid alternative investment products across a full range of strategies and regions. Learn more.
Data on 50M+ Private Companies
Soleadify is a leading global provider of data and analytics on small and midsize businesses (SMBs) and private companies. Using the latest in AI technology, Soleadify generates high-quality and recent data allowing better decision-making across underwriting, compliance, supply chain, and sustainability. The company is known for the high quality, recency, and depth of its data—which is used by some world’s largest banks, insurance companies, and consultants across numerous applications such as underwriting, lending, supply chain, compliance/KYB, and sustainability assessment. Learn more.
Investment Research & Consensus Estimates
Visible Alpha captures estimates and assumptions from full working sell-side financial models and creates detailed forecasts that go beyond the standard financial statements. It focuses on the key growth metrics and supplemental data that investment professionals use to better understand the factors driving company performance and stock price. Backed by the world’s leading investment banks, Visible Alpha is dedicated to creating the deepest consensus in the market, with more and higher quality sources, and longer-term forecast horizons. Learn more.
This post contains express and implied forwarding-looking statements, including statements regarding (i) Snowflake’s business strategy, (ii) Snowflake’s products, services, and technology offerings, including those that are under development or not generally available, (iii) market growth, trends, and competitive considerations, and (iv) the integration, interoperability, and availability of Snowflake’s products with and on third-party platforms. These forward-looking statements are subject to a number of risks, uncertainties and assumptions, including those described under the heading “Risk Factors” and elsewhere in the Quarterly Reports on Form 10-Q and Annual Reports on Form 10-K that Snowflake files with the Securities and Exchange Commission. In light of these risks, uncertainties, and assumptions, actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. As a result, you should not rely on any forwarding-looking statements as predictions of future events.
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