Snowflake Simplifies Data Application Development with Streamlit Acquisition



Join today’s top leaders online at the Data Summit on March 9. Register here.

Montana-headquartered Snowflake, which offers data warehouse and lake capabilities in a single “data cloud,” has taken another major step toward strengthening its platform for companies.

The company on Wednesday announced plans to acquire San Francisco-based Streamlit, a framework specifically designed to aid in the development of data applications. Terms of the agreement were not disclosed.

Streamlit’s Data Application Framework on Snowflake

While Snowflake started as a data warehouse provider in 2012, the company has evolved the product into a complete data cloud, which enables enterprises to unite their siled data, discover and securely share governed data and run various analytical workloads. Today, as the company explains, its data cloud acts as a solution for data warehousing, data lakes, data engineering, data science, data application development and data sharing.

Streamlit, on the other hand, is a younger player that operates in a particular area of ​​focus for Snowflake: data application development. The company’s open source framework simplifies and accelerates the creation of data applications without requiring front-end development experts. It has already been downloaded more than eight million times and has enabled the development of more than 1.5 million data applications and interactive data experiences.

With this acquisition, which is subject to customary regulatory approvals and closing conditions, Snowflake will be able to leverage Streamlit’s product and provide data scientists and developers with a better way to develop data applications within its cloud of data. Essentially, they will be able to use the ability of the Snowflake data cloud to discover data they can trust and the Streamlit framework as a single hub to build next-generation applications for AI/ML.

“This will make it easier for Snowflake customers to bring their data-driven applications to production, which has been an ongoing challenge in the field of data science and machine learning,” said Adam Ronthal, VP President of Research at Gartner’s ITL Data and Analytics Group. Venturebeat.

“Streamlit not only provides an application development framework, but also data visualization capabilities. It also reinforces Snowflake’s commitment to full support for Python – one of the most popular languages ​​used by data scientists – within the Snowflake platform,” he added.

Snowflake wants to become a data powerhouse

The acquisition of Streamlit, as mentioned above, represents an expansion of the Snowflake ecosystem. The company, which went public in 2020, enhanced its product’s capabilities by adding support for data science workloads and unstructured data, among others. Ultimately, it wants to be the hub of all data, a goal also pursued by players such as Databricks and Dremio.

“Providing tight integration for machine learning and data science initiatives is becoming a major challenge in the cloud data warehouse market. These features are often delivered through cloud-native service provider offerings like Amazon Sagemaker, Azure ML or TensorFlow.Sometimes they are provided through third-party offerings such as Django, Jupyter notebooks or more formally targeted AI/ML offerings such as DataRobot, KNIME, H2O or others.Streamlit (meanwhile) falls into the category of rapid application development for the AI/ML category,” said Ronthal.

This acquisition, he said, will allow Snowflake to provide a tightly integrated offering in the space. However, that won’t stop the company from continuing its existing partnerships and integrations with other competing offerings.

VentureBeat’s mission is to be a digital public square for technical decision makers to learn about transformative enterprise technology and conduct transactions. Learn more

Source link


Comments are closed.