While data is a core asset for modern enterprises, technology’s ability to scale has created a surge of big data. Managing and storing that data has become a critical function for modern business operations. Choosing a data platform that can handle massive volumes of big data, high speeds, and reliability — not to mention the ease of use, is top of mind. Most enterprises are already using a cloud data platform, but many are evaluating whether a data migration might be needed in order to stay competitive. One of the most popular data platforms is Snowflake, which operates as a cloud data warehouse and is heralded for its ability to support multi-cloud infrastructure environments. Snowflake is a data warehouse built on top of the Amazon Web Services or Microsoft Azure cloud infrastructure, and allows storage and compute to scale independently.
But, first… Before we get into why Snowflake has become so popular, let’s learn what its and how it works.
What is Snowflake?
Developed in 2012, Snowflake is a fully managed SaaS (software as a service) that provides a single platform for data warehousing, data lakes, data engineering, data science, data application development, and secure sharing and consumption of real-time / shared data. Snowflake features out-of-the-box features like separation of storage and compute, on-the-fly scalable compute, data sharing, data cloning, and third-party tools support in order to handle the demanding needs of growing enterprises.
Bonus fact: Snowflakes’ name was chosen as a tribute to the founders’ (Benoit Dageville, Thierry Cruanes, and Marcin Żukowski’s) common love for skiing.
What makes up the Snowflake platform?
How Snowflake is designed is through three main components. These are the foundation for Snowflake’s cloud data platform:
- Cloud services. Snowflake uses ANSI SQL for cloud services empowering users to optimize their data and manage their infrastructure. Snowflake handles the security and encryption of stored data. They maintain robust data warehousing certifications such as PCI DSS and HIPAA. Services include authentication, infrastructure management, query parsing and optimization, metadata management, and access control.
- Query processing. The compute layer of Snowflake is made up of virtual cloud data warehouses that let you analyze data through requests. Each Snowflake virtual warehouse is an independent cluster and they do not compete for computing resources nor affect the performance of each other — which means workload concurrency is never a problem.
- Database storage. A Snowflake database is where an organization’s uploaded structured and semistructured data sets are held for processing and analysis. Snowflake automatically manages all parts of the data storage process, including organization, structure, metadata, file size, compression, and statistics.
What are the benefits of using Snowflake?
There are multiple benefits to choosing Snowflake, including:
- Instant, nearly unlimited scalability. Snowflake architecture uses a single elastic performance engine that delivers high speed and scalability. Snowflake supports as many concurrent users and workloads as you can throw at it, from interactive to batch. This powerful ability lies in its multi-cluster resource isolation. It’s high-performing and robust, giving enterprises the confidence they need that they’ll be able to handle every data workload.Snowflakes’ single engine powers everything from complex data pipelines, analytics, feature engineering, interactive applications across essential data workloads. With SQL query support and the Snowpark developer framework for Java and Scala access, Snowflake makes it easy for users with all skillset levels to leverage data.
- Automation made easy. Enterprises no longer have time for manual data management and maintenance; they must move fast and accurately. Automation makes this possible. Snowflake enables enterprises to automate data management, security, governance, availability, and data resiliency. This drives scalability, optimizes costs, reduces downtime, and helps improve operational efficiency. It’s built for high reliability and availability and it automates data replication for fast recovery.
- A single copy of data, shared securely, anywhere. Snowflake eliminates ETL and data silos, with seamless cross-cloud and cross-region connections and data sharing. Anyone who needs access to shared secure data can get a single copy via the data cloud, with the confidence that governance and compliance policies are in place. With a single shared data source, teams across the enterprise and the business’s ecosystem can be sure they are working from a single source of truth, making remote collaboration and decision-making fast and easy.
- Third-party data integrations. Additionally, the Snowflake Data Marketplace offers third-party data and lets you connect with Snowflake customers to extend workflows with data services and third-party applications. An integration platform as a service (iPaaS) like SnapLogic makes integrating third-party data sources easy and automated. SnapLogic’s pre-built Snowflake connectors make it easy for anyone to create data pipelines to automate workflows across the enterprise.
What is Snowflake’s pricing model?
Traditional data warehouse software is built on existing on-premises databases or software platforms. Snowflake was designed to leverage the opportunities of mass cloud data storage and is built on Amazon s3. They offer a flexible pricing model where you pay for the compute and cloud storage that you actually use. They offer multiple pricing options for Snowflake accounts including on-demand per-second pricing with zero long-term commitments or pre-purchased Snowflake capacity options. Compute usage is billed on a per-second basis, with a minimum of 60 seconds. They offer a free trial period.
Can I integrate data into Snowflake with SnapLogic?
SnapLogic and Snowflake have joined forces to simplify data integration and data warehousing via the cloud. SnapLogic offers a fast, easy, and visual integration platform that helps customers integrate their on-premises and cloud-based data sources and applications without any coding. SnapLogic now offers ten pre-built “Snaps” that connect multiple data sources and analytics tools to the Snowflake cloud data warehouse solution. The data integration with Snowflake includes Snaps for bulk load, upsert, and unload in addition to standard CRUD (create, read, update, and delete) functionality. SnapLogic’s intelligent integration platform provides Snaps to easily connect multiple data sources (including Teradata, Oracle, MySQL) and applications (including Salesforce, Workday, Twitter) to Snowflake without any coding.