Snowflake for
DATA ENGINEERING
Powerful and streamlined pipelines with the ease and performance of Snowflake.
OVERVIEW VIDEO:
DATA ENGINEERING FOR PERFORMANCE, SIMPLICITY, AND RELIABILITY
Easily ingest, transform, and deliver your data for faster, deeper insights. With Snowflake, data engineers can spend little to no time managing infrastructure, avoid capacity planning and concurrency handling, and focus on building reliable, enterprise-ready data pipelines in a single platform.
Why Snowflake
for Data Engineering
SIMPLE OPTIONS FOR NEARLY EVERY PIPELINE USE CASE
Build streaming and batch data pipelines on a single platform with the power of declarative pipelines and automatic adjustments for compute.
Data Sharing → Fewer Pipelines
Access live, ready-to-use data directly from thousands of datasets and apps from Snowflake Marketplace, without having to build pipelines.
One place. All the power and flexibility
Program with your language of choice and deploy Snowflake’s multi-cluster compute engine. No separate infrastructure required.
Streaming Pipelines
Removing the barriers between streaming and batch systems. Building streaming pipelines with serverless ingestion and declarative transformation with just a few lines of SQL. Easily adapt to your business requirements with a single latency parameter change.
HOW SNOWFLAKE
ENABLES MODERN DATA
ENGINEERING
Latency Setting is like a single tuning knob
Modern data-driven applications can’t wait for data. Snowflake handles both batch and streaming data ingestion and transformation with a unified architecture.
- Load files in a serverless manner with Snowpipe.
- Ingest rows for streaming data with Snowpipe Streaming (Public Preview).
- Transform data with declarative pipelines using dynamic tables (Public Preview) for incremental refreshes. No need to define tables. They are created based on the output of the SELECT statement.
- Simply load data and run with auto-schema detection and evolution.
Build Fewer Data Pipelines By Collaborating in the Data Cloud
Being part of the Data Cloud means your organization has access to an ecosystem of data, data services, and applications with built-in, usage-based monetization via Snowflake Marketplace.
- Access ready-to-query data in the Data Cloud, eliminating unnecessary copies and data movement.
- Reduce the risk, cost, and headache from traditional data sharing and data pipelines.
- Bring in data through native connectors via Snowflake Marketplace.
Streamlined Architecture, No Tradeoffs
Streamline pipeline development and management with Snowflake. Avoid separate infrastructure required for different languages, and enable processing with a single compute engine.
Collaborate and bring users together with different coding preferences thanks to Snowflake’s developer framework, Snowpark, and our native support for ANSI SQL.
Build with Python, Scala, and Java; expand more functions; and execute faster in Snowflake with no additional processing systems needed.
Continuously optimize pipeline performance and price with instant resizing of dedicated compute clusters.
Apply consistent controls with zero governance or security trade-offs.
Automate data pipelines with serverless features.
Snowpark
Use Python, Java, or Scala, with familiar DataFrames and custom function support to build powerful and efficient pipelines, machine learning (ML) workflows, and applications. And gain the performance, ease of use, governance, and security that comes from working inside Snowflake's Data Cloud.
Hear from
Our Customers
Snowpark will allow us to modernize and consolidate our data engineering pipelines, simplify our architecture with an easy transition from Spark, and allow our data engineering team to continue working with their preferred development interface, a DataFrame API with lazy evaluation, despite changing underlying platforms. This is a win-win, reducing time to insight for our customers while making processes easier and cheaper to manage for us.
MOHIT SAUHTA
IT Architect Director
We don’t need to go down the Spark road anymore because Snowflake is a scalable, reliable, and secure foundation for our advanced business intelligence and data science use cases.... Our Spark architecture wouldn’t have worked; it has to be Snowflake.
PATRICK CALLINAN
Director of Insights and Data Science
Key for us [is that] they allow our business partners to have both control of their data while making it accessible to others, without having to move it around and duplicate it, and have all the latency issues and duplication issues that come with that.... AT&T has data at our fingertips.
Kate Hopkins
VP, Data Platforms
EXTENSIVE PARTNER
ECOSYSTEM
Choose from an extensive ecosystem of data integration partners.
Get Started
Building with Snowflake
Find the resources you need to build apps, data pipelines, and ML workflows at the Snowflake Developer Center
Explore Data Engineering
With Snowflake
WAYS TO
get started
Start Your 30-Day
Free Trial
Try Snowflake free for 30 days and experience the Data Cloud that helps eliminate the complexity, cost, and constraints inherent with other solutions. Available on all three major clouds, Snowflake supports a wide range of workloads, such as data warehousing, data lakes, AI and machine learning.
EXPLORE OTHER
WORKLOADS
Eliminate data silos and instantly and securely share governed data across your organization, and beyond.