Developers can now use Python within Snowflake
Late last year, US data solution software Snowflake announced that it now supports Python – the fastest growing programming language. For many users, this is the update we’ve all been waiting for. This post is going to cover everything you need to know about the new update, including what’s new, companies’ opinions and extra developments you can take advantage of in your next project!
What is Snowflake?
Snowflake is a solution software that enables organizations to mobilize their data with the cloud. Customers use the software to discover and share data whilst executing diverse analytic workloads. Its developer framework has helped data scientists, engineers and application developers collaborate effortlessly and to streamline their data architecture. It has brought teams together to collaborate on data in their own coding languages.
What is Python?
Python is a high-level programming language with dynamic semantics. It is used in the scripting of glue language to connect existing components together. Python’s simple syntax is popular amongst users and therefore reduces the cost of program maintenance.
Snowflake + Python: what’s new?
Late last year, US data solution software Snowflake announced that it now supports Python – the fastest growing programming language. It is now available within Snowflake, as a part of Snowflake, Snowflake’s developer framework. This means developers can collaborate on data in their preferred language if that is in fact Python. Simultaneously, they can leverage Snowflake’s platform to build scalable and optimized pipelines and machine learning workflows.
Users will be glad to know that Snowflake still supports Java and Scala, allowing users to work within the remits of different languages and still being able to work collaboratively against the same data with one processing engine. There is now no need to copy or move the data. This is a great step forward in Snowflake’s development as it means developers now have more flexibility to work in a simple environment which requires less admin work and less maintenance.
SVP of Product at Snowflake, Christian Kleinerman said: “Snowflake has long provided the building blocks for pipeline development and machine learning workflows, and the introduction of Snowpark has dramatically expanded the scope of what’s possible in the Data Cloud.”
“As with Snowpark for Java and Scala, Snowpark for Python is natively integrated into Snowflake’s engine so users can enjoy the same security, governance and manageability benefits they’ve come to expect when working with Snowflake. As we continue to focus on mobilizing the world’s data, Python broadens even further the choices for programming data in Snowflake, while streamlining data architectures,” Kleinerman added.
Snowflake for Python
Many companies have stepped forward and expressed their excitement and support of this new update, describing how this has helped internal teams collaborate.
Canva’s Head of Platforms Greg Roodt has detailed how their team is taking advantage of the new technologies Snowflake provides. He said Canva had previously used a platform that only offered fixed costs, which proved difficult as Canva grew in size so quickly.
“Our rate of growth is high, but Snowflake supports us – we don’t have those awkward conversations we used to with our previous vendor,” Roodt said. “With Snowflake we’re able to pay for what we use and keep adding to that if we need more capacity.”
Global healthcare company Novartis has also described why they use Snowflake. Global Head of Digital Platform & Product Delivery Loic Giraud has said “the flexibility and scale of Snowflake’s Data Cloud allows us to accelerate our pace of knowledge through data interpretation and insight generation, bringing more focus and speed to our business. Bringing together all available data ultimately unlocks more value for our employees, patients, and healthcare providers, and data science innovations help us realize this goal”.
With Snowflake for Python, users can take advantage of the following nifty benefits:
- Accelerate their pace of innovation – Python’s familiar syntax and ecosystem of open-source libraries means users can explore and process data where it lives
- Optimise development time – broken Python environments are a thing of the past with this update. An integrated Python package dependency manager erases any problems of this caliber allowing optimum development time.
- Operate with improved security – this new update means users can eliminate ungoverned copies of data with all code running in a secure sandbox inside of Snowflake.
Growing Data Cloud Adoption
There are many developments within Snowflake, including the growing data cloud adoption. Let’s have a look at some of the new developments.
Firstly, new developments within Snowflake for Python include cross-cloud account replication. Snowflake’s native database replication (which covers everything from identity to role-based access controls) cannot be synchronized across clouds and regions for availability. This ensures point in time consistency with the primary region.
Secondly, there is also improved replication performance. A 55% increased performance improvement is thanks to its increased efficiency of data replication. This, in turn, translates to a 55% reduction in customer replication costs because Snowflake users only pay for what they use.
Expanded governance capabilities and integration are also another development of the Snowflake for Python update. New capabilities can help compliance teams track and more importantly, understand their sensitive data. It supports an entire ecosystem of partner-delivered solutions and integrations to protect data.
Finally, Snowflake introduced unstructured file processing in this update. Using Java functions directly in the program, users can now leverage its performance, scale and security, unlocking new cases, natural language processing and more.
Snowflake directly states “As part of the Snowpark for Python offering, we wanted to bring enterprise-grade open source innovation to the Snowflake Data Cloud while helping ensure a seamless experience for data scientists and developers to do their work. Through our recent Anaconda partnership and product integrations, this seamless experience is now a reality”.
So, there you have it, everything you need to know about the Snowflake for Python update and more! The new update has enabled innovation and collaboration beyond belief and users across the globe are already reaping the benefits of such an update. If you’d like to also reap the benefits of the Snowflake for Python update, get started by requesting a consultation with us.