The Snowflake Data Warehouse is a robust, cloud-built data platform delivered as a service.
A single place for Data
Scale & Concurrency
Near zero management
Instant, live data sharing
Cross-Cloud Deployment Capabilities
Cross-Cloud Deployment Capabilities support your multi-cloud strategy in the following cloud platforms: Amazon Web Services (AWS), Microsoft (Azure), and Goodgle (GCP).
Leveraging a multi-cloud strategy enables your organization to avoid vendor lock-in while taking advantage of the varying services that the major cloud providers offer, especially around security, applications, and analytics services.
Separate workload clusters
Separate workload clusters enable the ability to separate compute clusters against the same data with both consistency and integrity.
The ability to separate workloads can support data scientists and data analysts as well as analytics and reporting, IT workloads, and various other workloads with one platform while providing a single source of truth.
Virtually unlimited query concurrency supports simultaneous operations.
Snowflake can scale with virtually unlimited computing capacity to handle even your most robust peak demand.
High performance queries on JSON.
Snowflake provides the ability to get a holistic view of your organization with more advanced insights by leveraging the capability to run JSON queries more efficiently.
High performance queries across a broad range of structured data types.
Snowflake provides the ability to get a holistic view of your organization with more advanced insights by leveraging the capability to run JSON queries more efficiently.
Quickly scale up & down (vertically), out & in (horizontally), or off, without disruption.
Your organization will be able to elastically scale the Snowflake data warehouse resources easily and without any disruption to queries that are currently running. In addition, you will benefit from the cost efficiencies of not incurring compute charges when your Snowflake compute is idle.
Automatic database management.
Snowflake is delivered as a service, eliminating the time and effort of managing data warehouse infrastructure.
No parameters, no distribution, key management, no tuning, no vacuuming.
Snowflake supports organizations to maximize their valuable data engineering resources, eliminating tedious tasks and the need to spend their limited time on higher-value data engineering projects.
Complete SQL database and data warehouse
Snowflake is a robust, enterprise-grade ANSI SQL and provides the best compatibility with your enterprise data warehouse applications, in addition to including multi-statement transaction support.
Built-in high availability data protection and data retention
Snowflake has the capability to retain and recover data up to 90 days, which protects your organization against node failures, human errors, unfortunate events, and malicious attacks.
Cost-effective data storage pricing
Data storage in a compressed format at a very budget-friendly cost and as expensive premium storage is not required for Snowflake.
The Snowflake Cloud Data Platform is redefining what it means to be a cloud data warehouse, as well as providing capabilities that are unmatched by others in the marketplace.
Our customers are both leveraging the advantages of Snowflake to focus on strategic decision-making and becoming data-driven organizations, respectively. Success with Snowflake will lead to building a data foundation that future initiatives can build on to further advance and grow the organization’s data and analytics capabilities.
Snowflake vs Azure E-Book
Data Ideology has created a Free Comprehensive E-Book that highlights many of the key differences, advantages and disadvantages to consider when starting your Cloud Data Migration Journey.
Learn More
FAQs
All Your Data, All Your Users
What are the advantages of Snowflake data warehouse? ›
Some advantages of using Snowflake are:
- Scalability: Easily scale resources to match your data needs without affecting performance.
- Cost-efficiency: Pay only for the storage and computing resources you actually use.
- Flexibility: Compatible with a wide range of data formats and integrates with popular tools.
Snowflake enables data storage, processing, and analytic solutions that are faster, easier to use, and far more flexible than traditional offerings. The Snowflake data platform is not built on any existing database technology or “big data” software platforms such as Hadoop.
What are the competitive advantages of Snowflake? ›
Efficiency and Scalability:
Businesses can grow resources dynamically because to Snowflake's elasticity and the division of computing and storage. This benefit is maximized by Helical IT Solutions, which aids businesses in adapting to changing data requirements without sacrificing effectiveness.
What is snowflake schema and its advantages? ›
The snowflake schema is useful for organizing and querying large, complex databases because it allows for more efficient querying and faster performance. It is often used in data warehouses and business intelligence applications, where the focus is on analyzing and reporting large amounts of data.
What are 3 advantages of data warehouse? ›
These are just a few advantages that data warehousing offers for your business. It provides improved business intelligence, robust decision support, superior business practices, and effective analytics processing.
Why is Snowflake better than other data warehouses? ›
Snowflake has a micro-partitioning storage architecture that organizes data in columns, meaning analytics queries can run much faster in Snowflake than they might in a traditional SQL (Structured Query Language) database.
How is Snowflake different from other data warehouses? ›
Traditional data warehouses are typically implemented using a “shared-nothing” architecture, which means that data is partitioned and distributed across multiple nodes, each with its own CPU, memory, and storage. In contrast, Snowflake uses a hybrid of traditional shared-disk and shared-nothing architectures.
How is Snowflake different from big data? ›
BIG DATA AND SNOWFLAKE
Snowflake is the strongest of the Hadoop alternatives in big data management. Through its partnership with cloud Big Data as-a-service-company Qubole, Snowflake maximizes its data warehouse potential. The partnership enables customers to use Apache Spark in Qubole with data stored in Snowflake.
What is the best feature of Snowflake? ›
14 Key Features of Snowflake
- Near-Zero Management. Snowflake offers near-zero management because it's a cloud-based, fully managed platform that requires no hardware to select, install, configure, or manage. ...
- Scalability. ...
- Cloning. ...
- Time Travel. ...
- Fail-Safe. ...
- Data Sharing. ...
- Data Caching. ...
- Availability.
Snowflake wins on ease of setup, but Databricks was designed for more advanced users and AI/ML use cases, which require more robust ETL, data science, and machine learning features. The complexity cuts costs in the long run, as it can be scaled up without upgrades.
Why Snowflake is better than SQL? ›
Snowflake uses a schema-less approach to data modeling, which allows users to easily store and query data without the need for predefined schemas. SQL Server, on the other hand, uses a traditional relational data modeling approach that requires the creation of schemas before data can be stored.
What are the advantages of Snowflake over AWS? ›
Snowflake is the apparent winner compared to AWS Redshift in terms of maintenance because its separate storage and compute architecture makes it easier to scale up and down. You can change a warehouse's size or increase the number of clusters.
Why is Snowflake powerful? ›
Thanks to the separated storage and compute, Snowflake has the ability to run a virtually unlimited number of concurrent workloads against the same, single copy of data. This means that multiple users can execute multiple queries simultaneously.
What are the advantages and disadvantages of snowflake schema? ›
Advantages and Disadvantages of Snowflake Schema
Normalization also helps in making query handling more efficient. Snowflake also helps in preventing data repetition. Its main downside is its complexity and performance resulting in many small dimension tables that convolute the data warehouse design and maintenance.
What are the advantages of Snowflake over Oracle? ›
Snowflake vs Oracle solution strategy is a comparison of the two software solutions to determine which is best suited for a particular business. For example, Snowflake offers scalability, easy deployment, and cost-effectiveness, while Oracle provides advanced analytics capabilities with customizable SQL scripts.
What are the benefits of Snowflake over SQL? ›
Snowflake uses a schema-less approach to data modeling, which allows users to easily store and query data without the need for predefined schemas. SQL Server, on the other hand, uses a traditional relational data modeling approach that requires the creation of schemas before data can be stored.
What are the advantages of Snowflake stored procedure? ›
Benefits of Snowflake Stored Procedures
- Enhanced performance: Stored procedures improve performance by reducing network latency and processing overhead.
- Code reusability: Encapsulate business logic and reuse code across multiple applications or processes.
A warehouse provides the required resources, such as CPU, memory, and temporary storage, to perform the following operations in a Snowflake session: Executing SQL SELECT statements that require compute resources (e.g. retrieving rows from tables and views).
What is the advantage of Snowflake over redshift? ›
Snowflake is the apparent winner compared to AWS Redshift in terms of maintenance because its separate storage and compute architecture makes it easier to scale up and down. You can change a warehouse's size or increase the number of clusters.
