Snowflake’s cloud data platform combines the power of data warehousing, the flexibility of data lakes, and the near-infinite resources of the cloud. You can choose to land your data in Snowflake as your central repository and experience the highest level of performance, relational querying, security, and governance. Or, you can land your data in cloud storage from Amazon S3, Azure Data Lake Storage, or Google Cloud Storage and use Snowflake to accelerate data transformations and analytics in your existing data lake.
Organizations that deploy and manage complex computing environments contend with slow performance, lack of data governance, and the headache of maintaining incomplete data security. These are the struggles organizations face today when using generic cloud storage environments or Hadoop-based solutions as their data lakes. The result is significant overhead to manage these systems, the inability to get all the insight from all your data, and the increased possibility of putting your data at risk.
The data lake from Snowflake supports structured and semi-structured data in the same data platform and has the following benefits:
Performance:
With Snowflake’s multi-cluster shared data architecture, experience dramatically better performance compared to Hive-on-Hadoop or Spark-on-cloud storage data lake approaches.
Near-zero maintenance:
From instant non-disruptive scaling, to schema-on-read data transformations, focus on delivering data-driven value to your users and communities – not managing infrastructure.
Choose your solution:
Land data in Snowflake or supercharge an existing data lake to eliminate traditional data lake struggles and deliver superior ease-of-use.
Support all your data:
Natively ingest all of your structured and semi-structured data (JSON, Avro, and XML) into Snowflake, or leave that data in your data lake and query it with Snowflake’s robust ANSI SQL.
Use schema-on-read:
Use Snowflake’s schema-less data ingestion to avoid unnecessary delays when loading data from your data lake to Snowflake. Or, use Snowflake’s external tables to access files directly from your data lake.
Capture data updates, faster:
Configure Snowflake external tables to automatically refresh as the data in your data lake changes. New data is readily available for analysis without expensive and time-consuming overhead.