Snowflake for
DATA ENGINEERING
Powerful and reliable 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.
Why Snowflake
for Data Engineering
All Data at Speed With An Open Ecosystem
Collaborate in the Data Cloud with access to an open data ecosystem with streaming, batch, structured, and unstructured data, all in a single platform.
Performance and Reliability at Scale
Run enterprise-ready data pipelines with near-instant scalability and virtually no resource contention, powered by the elastic performance engine.
Radically Simple Data Pipelines
Simplify and eliminate unnecessary pipelines with intelligent infrastructure, pipeline automation, and data programmability.
HOW SNOWFLAKE
ENABLES MODERN DATA
ENGINEERING
Batch and Streaming Data Pipelines with an Open Data Ecosystem
Modern data-driven applications can’t wait for data. Snowflake handles both batch and continuous data ingestion of structured, semi-structured, and unstructured data.
- Access ready-to-query data in the Data Cloud.
- Get native support for semi-structured and unstructured data in a single platform.
- Ingest data in a serverless manner with Snowpipe and Snowpipe Streaming (in private preview) for real-time data pipelines.
- Simplify change data capture (CDC) with Snowflake’s Streams and Tasks.
- Simply load data and run with auto-schema detection and instant data availability.
Performance at Scale with Tailored Transformation Needs
Traditional solutions require dedicated time windows for executing pipelines. On the flip side, Snowflake is uniquely architectured to provide multi-clustered computing, with resource isolation for each workload, in a secure and governed platform.
- Maintain performance across a near-infinite number of concurrent workloads thanks to Snowflake’s multi-cluster shared data architecture.
- Process with Snowflake’s elastic performance engine for data transformation workloads.
- Only pay for what you use by optimizing pipeline performance and price, with instant resizing of dedicated compute clusters.
- Scale a near-infinite amount of computing resources, up or down, with just a few clicks.
- Gain trust with Snowflake's consistent and strong governance and security protocols.
Simplified Data Transformation and Architecture
Streamline pipeline development and management with Snowflake, with less time spent on managing infrastructure, and no more unnecessary data pipelines.
- 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.
- Build resilient data pipelines with Schema-on-Read and without the need to define schema in advance.
- Enable your other workloads with Snowflake: data warehouse, data lake, unistore, collaboration, cybersecurity, data science & ML, and applications.
- Easily and securely share and consume live, governed data in real time.
- 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
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, and data science.
EXPLORE OTHER
WORKLOADS
Eliminate data silos and instantly and securely share governed data across your organization, and beyond.