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Data Lakes

Turbocharge data lake analytics

Many organizations have or will have in place a cloud-based data lake to ingest and store data from a variety of disparate data sources. But in order to maximize the utility of a data lake, you need to do something with the data and objects stored in it. You want to create real-time dashboards to report on the data, run fast analytics to uncover insights and relationships, interactively explore the data to find new trends, and much more. And, you want to accomplish all this across multiple workgroups and stakeholders that need to access the data concurrently.

Executing these broad set of use cases requires more than the typical unlimited storage capacity and convenient data access capabilities that traditional data lakes excel at offering. You need a highly performant, relational database and data warehouse. Snowflake–the only data warehouse built for the cloud and delivered as a service–provides a complete solution capable of high performance, low-latency relational analytics, self-service capabilities, as well as virtually unlimited multi-workgroup concurrency scaling–all from one environment.

In addition, with Snowflake you have the power and flexibility of both worlds. You can land data such as JSON, XML, and Avro, including Parquet data stores, directly in Snowflake. No external data lake required. Or you can land your data in a cloud blob store like Amazon S3 or Azure Blob Storage and turbocharge the data lake with Snowflake and achieve up to 100X performance compared to running relational queries from the data lake. No ETL effort, pre-transformations or pre-schemas required. 

  • Support all your data

    Natively ingest semi-structured data (JSON, Avro, XML, and more) from data sources, events or applications without transforming the data first. Immediately query the data with robust, relational ANSI SQL.

  • Support all your users

    Easily scale and allocate resources to different workgroups without data or resource contention. Take advantage of Snowflake’s elastic, automatic scaling to eliminate concurrency limitations.

  • Support a multitude of use cases

    From traditional data warehousing and business intelligence reporting, to real-time dashboards and live analytics, to interactive data exploration and more, Snowflake can handle diverse use cases with ease and simplicity.

A data lake with ACID-compliant, ANSI SQL

Times are changing. When you want to build a data lake in the cloud, you don’t have to compromise having an enterprise data warehouse too. Learn how in our solution brief.

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Video

Modern cloud data warehouse-as-a-service vs. Hadoop

Snowflake SME explains why a modern data warehouse, built for the cloud, can provide superior capabilities for data lake use cases.

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Data Sheet

Big Data does not have to equal Big Effort

What if you could have the flexibility of Hadoop without the complexity, the fastest EDW without the cost, and an environment as easy to set up and manage as a desktop app - all built in?

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Customer Video

Rue La La drives personalized marketing from Snowflake data lake

Rue La La consolidates multiple customer and corporate data platforms onto a single Snowflake data lake built for the cloud and now has a full view of its customers.

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  • After combining our data lake and data warehouse onto Snowflake, our marketing department now has the unique ability to have a 360o view of our customers. They will be able to do better targeted marketing to our members and promotions targeted at members.

    – Erick Roesch, Director of BI & Data Warehouse, Rue La La