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What You'll Learn
What is Snowflake?
Developed in 2012, Snowflake is a modern data platform that operates as a cloud-based data warehouse for data storage, processing, and analytics. It is built on top of Google Cloud, Microsoft Azure, and Amazon Web Services, and can support multi-cloud infrastructure environments.
Snowflake is a fully self-managed software-as-a-service solution with a single platform for data warehousing, data engineering, data science, data application development, AI/ML deployment, and more. It enables all of this while securing data sharing within your organization.
When we say that Snowflake is a fully self-managed data platform, it means that there’s no need to select, install, configure, or manage any physical or virtual hardware. You don’t need to install or configure any software. The best part? The platform will handle all ongoing maintenance, management, and upgrades.
The Snowflake data cloud platform supports different languages such as SQL, Python, Java, and Scala. The types of data architecture patterns supported are data warehouses, data lakes, a hybrid of data warehouse and data lake, and data mesh.
Inside Snowflake Architecture
The Snowflake Data Cloud Platform has elements of both shared-disk and shared-nothing database architectures.
Snowflake stores all data in a central location, like shared-disk systems. This enables all compute nodes to access it.
However, like shared-nothing systems, the Snowflake platform uses massively parallel processing clusters where each compute node handles part of the data locally to process queries.
Snowflake’s architecture is built on three key layers:
Image Credit: Snowflake
In this layer, the data is divided into smaller units called micro-partitions. For instance, if the data is a table of transactions, each day of transactions is stored as a separate micro-partition or file.
Compute Layer
Executes SQL statements using independent compute clusters, called virtual warehouses. They process queries in parallel. Each virtual warehouse is equipped with CPU, memory, and temporary storage to perform SQL and Data Manipulation Language tasks.
Services Layer
This layer manages key functions that coordinate tasks across the Snowflake platform. These services include authentication and access control, managing virtual warehouses and storage, handling metadata, and optimizing queries.
Key Statistics & Facts about Snowflake
- Snowflake is one of the largest cloud vendors by revenue as of 2023.
- Snowflake’s revenue topped 2.8 billion U.S. dollars in its financial year ending January 31, 2024.
- The AI Data Cloud platform serves approximately 10,249 global customers across different industries.
- 7200+ brands mobilize their data with Snowflake.
- Snowflake is the #1 data warehouse platform with a total of 19.24% market share.
Why Consider Migrating to Snowflake – 5 Best Reasons
1. Store & Analyze All Types of Data
Snowflake platform can store all structured, semi-structured data and provides native support for file formats such as CSV, JSON, AVRO, PARQUET, XML, Apache ORC, and more. It also provides additional support through Snowpark to secure, govern, query, and analyze unstructured data like text-heavy, form responses and social media conversations, images, video, and audio files.
2. Enable Quick, Real-Time Analytics
When your data is uploaded in Snowflake, it automatically gets reorganized into an optimized, compressed, and columnar format. The columnar databases do not require a lot of memory to output data. What does this mean? You can store more data and queries will be faster, resulting in better processing of big data. This, in turn, accelerates data analytics.
3. Scale Seamlessly with Near-Zero Maintenance
Snowflake elastic performance architecture is designed to support any number of users, jobs, or data with multi-cluster resource isolation. Compute resource scaling is separated from storage resources. Compute resources can scale without disruption while queries are running.
There’s no need to redistribute data storage. Concurrent workloads can run without impacting each other. For storage, virtual warehouses can be started or stopped at any time.
4. Eliminate Upfront Costs with Consumption-Based Pricing
Snowflake offers a pay-as-you-go pricing model. This means that you will only need to pay for the storage and computing resources that you’ll be using for your migration project. Get auto-scaling to optimize resource allocation. Snowflake’s data sharing feature help you reduce data duplication and lower storage and management costs. Its cloud-native architecture simplifies infrastructure management and lowers operational overhead.
5. Enable Enhanced Data Security
The Snowflake Data Cloud Platform automatically encrypts data both at rest and in transit. Each table partition is encrypted with its own unique key in a hierarchical model. How it’s useful? It minimizes risk by limiting the amount of data protected by any single key.
Snowflake provides an option for customers to manage their own encryption keys using a feature called Tri-Secret Secure. Even without this feature, Snowflake automatically changes encryption keys every 30 days.
The LumenData Advantage for Snowflake Migration
If you consider going for Snowflake, we have vast expertise that can aid you in your decision making and can help you set up a migration strategy. Our team can help you with faster deployment with 95% risk mitigation. LumenData is a proud premier services partner with Snowflake and together we’ve enabled several large customers to migrate their data infrastructure to the cloud and grow their instances.
Customizable offerings for data warehouse modernization, visualization & analytics, and managed services.
Services for Snowflake Streams, SnowPark, SnowPipe, Streamlit, & more.
Expertise in driving Gen AI-enabled migration to Snowflake.
SaaS accelerators for rapid data warehouse migration from legacy, superpipe for high-speed data ingestion.
Highly Skilled Team with 75+ Snowflake Certifications
Want to get the most out of Snowflake? Connect today.
About LumenData
LumenData is a leading provider of Enterprise Data Management, Cloud, and Analytics solutions and helps businesses handle data silos, discover their potential, and prepare for end-to-end digital transformation. Founded in 2008, the company is headquartered in Santa Clara, California, with locations in India.
With 150+ Technical and Functional Consultants, LumenData forms strong client partnerships to drive high-quality outcomes. Their work across multiple industries and with prestigious clients like Versant Health, Boston Consulting Group, FDA, Department of Labor, Kroger, Nissan, Autodesk, Bayer, Bausch & Lomb, Citibank, Credit Suisse, Cummins, Gilead, HP, Nintendo, PC Connection, Starbucks, University of Colorado, Weight Watchers, KAO, HealthEdge, Amylyx, Brinks, Xylem, Clara Analytics, and Royal Caribbean Group, speaks to their capabilities.
For media inquiries, please contact: marketing@lumendata.com.
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