Snowflake announces Python support in Snowpark. Until today, the latter solution made Scala and Java available for the development of data pipelines and data-intensive applications. Now, Python joins the ranks.
Snowflake’s platform entails a complete data stack. This includes tooling for developing data pipelines, setting up data lakes, structuring in data warehouses and developing applications that depend on a data stream.
Snowpark, a complementary solution, aids the development of data pipelines and data-intensive applications by answering two needs. First, the solution enables users of SQL to incorporate Java functions into applications. Secondly, users of the programming language Scala have the option of developing data pipelines in applications without the intervention of SQL, which reduces dependence on the latter programming language.
Python in Snowpark
Snowflake added a third functionality to Snowpark. As of today, data in Snowflake is entirely approachable with Python. The programming language can be used to drive and harness Snowflake data independently of SQL. Both syntax and a range of popular Python libraries are supported.
The introduction points to a trend. Snowflake is moving away from the entrenched relationship between SQL and data engineering. With Snowpark, the organization aims to support a wider range of programming languages. The latter was previously underlined by Scala and Java, now with Python. The question is not whether more languages fit the bill, but which one turns out to be next.
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