Cross-platform data transaction and analysis
Snowflake introduces new triple for data cloud
providers on the subject
Snowflake announced new products for its Data Cloud at the recent Las Vegas Summit, including a modern approach to collaboration on transactional data and analytics, a new public platform for developers, and the expansion of native Python support.
Torsten Grabs, Director of Product Management at Snowflake in Bellevue, said they were real “highlights” ahead of the summit. He is particularly pleased with the Unistore Workload. Snowflake thus technically re-implements data manipulation and data analysis. So far, according to Grabs, transactional and analytics data has been stored separately in Snowflake or delivered through clients like Tableau. But having to move data between multiple systems or having to manage redundant data sets across multiple solutions – that’s really outdated. Today, shorter and less extensive analyzes as well as faster updates of smaller datasets are required.
With Unistore Workload, organizations can now use a single, unified data set to develop and deploy applications and analyze both transactional and analytical data together in near real-time. According to Grabs, delivery can also be done on non-BI systems. And – this is the real highlight – the whole thing on a single platform.
Early adopters are “enthusiastic”
Adobe is an early adopter of Unistore and uses the private preview of hybrid tables for the Adobe Campaigns app. “By deploying Adobe Campaigns on Snowflake, we are able to offer our customers unparalleled speed and scalability,” said Nick Hall, Senior Director, Adobe Campaign & Managed Cloud Services. “Our teams are already thrilled with the improvements we’re seeing, including a 50x improvement in lead time.” opens on a large scale.
Implementing different storage options, individually designing query masks, or being able to prepare queries in the backend for fast, targeted data delivery would have convinced early adopter companies, Grabs happily says. For example, other users such as UiPath or Novartis use Unistore to store application state for pipelines, provide online attribute stores, or secure enterprise transaction applications.
Improved scheduleability in Data Cloud
In a similar context is the new Native Application Framework, which was designed for application developers. The public platform enables the creation, monetization and deployment of data-intensive applications in the data cloud to drive user or business logic through the Snowflake Marketplace.
According to Snowflake, the Native Application Framework, which is in private preview, allows developers to build applications using Snowflake features such as stored procedures, user-defined functions (UDFs), and user-defined array functions (UDTFs ). Other features such as Streamlit integration for developing interactive customer interfaces and telemetry functions such as events and alerts for monitoring and troubleshooting are also under development. Because the Native Application Framework builds on Snowflake’s high availability and disaster recovery, global collaboration capabilities, and security posture, developers in the Data Cloud should be able to focus on functionality rather than features.
The addition of native Python support completes the trio of new announcements. Snowpark for Python is now available in public preview. This makes Python’s ecosystem of open source packages and libraries available to data scientists, data engineers, and software developers. Snowflake is investing heavily in Python to enable even more developer projects to grow in the data cloud without compromising governance, Christian Kleinerman, Snowflake’s senior vice president of products, said in a statement.
In addition, data access is set to be simplified with new options for using streaming data through native integration with Streamlit for rapid application development and deployment. The data cloud is also expanding to include open data formats and data stored on premises.