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What is Snowflake?
The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed,…
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What is Snowflake?
The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the…
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What is Amazon Redshift?
Amazon Redshift is a hosted data warehouse solution, from Amazon Web Services.
Product Demos
Snowflake Must Know New Objects | Chapter-8 | Snowflake Hands-on Tutorial
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Webinar: Snowflake on Azure: Modern Data Analytics
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Snowfall Projector Light
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Snowsight - Snowflake Modern Web UI | Chapter-5 | Snowflake Hands-on Tutorial
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Snowflake Database/Schema/Table & Container Hierarchy | Chapter-7 | Snowflake Hands-on Tutorial
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DesignsBySiCK.com Wash Away Fibrous Free Standing Lace FSL Snowflake demo
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Product Details
- About
- Competitors
- Tech Details
- FAQs
What is Snowflake?
The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.
Snowflake Data Marketplace gives data scientists, business intelligence and analytics professionals, and everyone who desires data-driven decision-making access to live and ready-to-query data from your ecosystem of business partners and customers, and from potentially thousands of data providers and data service providers.
Snowflake Data Marketplace gives data scientists, business intelligence and analytics professionals, and everyone who desires data-driven decision-making access to live and ready-to-query data from your ecosystem of business partners and customers, and from potentially thousands of data providers and data service providers.
Snowflake Screenshots
Snowflake Video
Product Introduction
Snowflake Competitors
- Amazon Web Services
- Databricks Lakehouse Platform
- · Google BigQuery
Snowflake Technical Details
| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
Frequently Asked Questions
The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.
Amazon Web Services and Databricks Lakehouse Platform are common alternatives for Snowflake.
Reviewers rate Support Rating highest, with a score of 9.8.
The most common users of Snowflake are from Mid-sized Companies (51-1,000 employees).
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Community Insights
TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!
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- Pros
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Snowflake is widely used by organizations as a data lake and data warehouse, allowing users to blend data from multiple sources and generate comprehensive reports without impacting transactional databases. Users appreciate the excellent built-in features of Snowflake, such as row-level security, data masking, and secure sharing, which enable them to implement robust security measures at the database level. The software's model of separating compute from storage and accommodating different workloads for different scenarios proves to be highly advantageous for users. Additionally, Snowflake serves as a central repository for data, providing a single source of truth and facilitating data engineering for various use cases. Users can easily connect with data service providers, make data-driven decisions, and create modern and integrated data applications. The cost-effectiveness of Snowflake simplifies online data handling and supply to customers. It is widely used by data analytics clients across various industries due to its efficient, scalable, and easy-to-use data environment.
Furthermore, Snowflake enables quick and effective data querying, allowing users to gain insights into program aspects and user behavior for smarter business decisions. Its architecture, scalability, and data sharing capabilities make it a reliable cloud-based data warehousing solution for managing and sharing data efficiently. Many organizations are leveraging Snowflake to build a centralized solution for their reporting and analytics efforts. Snowflake's separation of compute from storage and pay-as-you-go pricing model enable intelligent and efficient budget planning and use. Customers are also using Snowflake to drive machine learning projects and gain valuable insights into their business data.
In addition to serving as a primary data warehouse for organizations, Snowflake is also instrumental in powering dashboards, machine learning solutions, ad-hoc queries, daily KPI aggregation, predictive modeling, customer acquisition management, telemetry insights, and more. Data teams across different departments rely on Snowflake for their compute purposes. The software offers an impressive data compression rate and faster data retrieval compared to other solutions like Amazon Redshift, making it an ideal choice as an enterprise data warehouse. The ease of use and accessibility of Snowflake make it widely adopted across entire organizations, catering to users with varying levels of data science skill. From basic data munging and querying to deep machine learning analysis and real-time access to data, Snowflake powers the entire data warehouse for many companies, providing crucial analytical understanding of performance and influencing business strategy.
Intuitive User Interface: Users have consistently praised Snowflake's intuitive and easy-to-use interface, with many stating that it is beginner-friendly. The drag and drop feature for tables into queries has been particularly helpful for users when writing complex queries.
Advanced Security Features: Snowflake's security features have received high praise from users, who feel confident in connecting with numerous business partners due to the platform's advanced security measures and effective programming. This positive sentiment indicates that Snowflake successfully prioritizes data protection and privacy.
Seamless Data Integration: Users appreciate Snowflake's ability to integrate, analyze, and transfer data from multiple clouds. They find it easy to have a transparent idea about data extraction and transfer. This feature allows users to efficiently work with their diverse datasets across different cloud platforms without any hassle or complications.
Limited Reporting Tools: Some users have mentioned that the reporting tools in the software are limited, which has led them to rely on additional tools like Tableau for more advanced reporting capabilities. They feel that having more robust built-in reporting features would enhance their data analysis and visualization options.
Cloud-Only Data Warehouse: The fact that the data warehouse is entirely cloud-based has raised concerns for some businesses. They worry about potential issues with data security, privacy, and control. These businesses prefer an on-premises solution or a hybrid approach where they can have more direct control over their data storage.
Complexity of JavaScript Implementation: Users have noted that implementing stored procedures through JavaScript can result in unnecessary overhead if their team lacks expertise in this programming language. This creates challenges when it comes to developing and maintaining complex procedures, leading to frustration among users who prefer a simpler implementation process.
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Reviews
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July 16, 2023
Snowflake: a tool for all-level analysts
We use Snowflake to query data from AWS S3. SQL query is easy to use for all level of data analysts/data scientists and as a result, Python or R is not required to pull data from Snowflake. Snowflake is widely used in my organization from customer acquisition to customer management.
- Query.
- Easy to use.
- Low requirements.
- Data type.
- Speed.
- Integration.
Our company has grown organically and by acquisition, and as a result we have a series of disparate software products with around 800 databases across different clouds and different databases - SQL Server, MySQL, Postgres, AWS, Azure, etc.
My challenge was to implement an awesome and consistent reporting suite that allowed customers full access to all of their data across all of our products. While the software development team is working on integrating all these disparate products, that's a significant multi-year challenge.
Implementing a data lake in Snowflake greatly empowered my team to make tremendous reporting, blending data from many sources, without adding any load to the transactional databases. What's more, Snowflake has a vast array of excellent built-in features such as row-level security, data masking, secure sharing, and other items that allowed us to push security right down to the database level so we secure data no matter how customers access it, without relying on complex where clauses, etc., in queries.
The Snowflake model of separating compute from storage and allowing us to have differing workloads for differing usage scenarios is also very helpful.
My challenge was to implement an awesome and consistent reporting suite that allowed customers full access to all of their data across all of our products. While the software development team is working on integrating all these disparate products, that's a significant multi-year challenge.
Implementing a data lake in Snowflake greatly empowered my team to make tremendous reporting, blending data from many sources, without adding any load to the transactional databases. What's more, Snowflake has a vast array of excellent built-in features such as row-level security, data masking, secure sharing, and other items that allowed us to push security right down to the database level so we secure data no matter how customers access it, without relying on complex where clauses, etc., in queries.
The Snowflake model of separating compute from storage and allowing us to have differing workloads for differing usage scenarios is also very helpful.
- Security
- Scaling
- Support
- Separating compute from storage
- Flexible disparate compute models
- Detailed history of all your queries and activity, for analysis/review/troubleshooting
- Cloning, undeletion, sharing - all tied to how Snowflake stores data
- There is no support for triggers
- Materialised views are limited to only one table
- You can't create dynamic SQL in functions
March 09, 2023
Unleash the power of data with Snowflake - the cloud data platform built for the future
We have used Snowflake to ingest, store and process data from the customer devices telemetry data for various insights. Ease of creating a pipeline from multiple sources without worrying about the amount of data and scalability of compute for different departments helped us a faster go to market solution. Continuous discovery is the core of our team means fail fast with minimum cost, with Snowflake we are able to do quick proof of concept and align project goals to the organization strategy
- Ingestion from different cloud platforms like AWS, Azure and GCP
- Ability to store data in multiple formats including structured and unstructured
- Compute is dynamic. Ability to chose a compute based on cost and performance.
- Data visualization capability has improved though have lot of areas of improvement
- Data governance and catalog capabilities
December 21, 2022
Don't debate, just migrate to Snowflake already.
We use Snowflake in our organization as both our data lake & data warehouse. Instead of ETLing from source to a data lake to then architect our data, we have made internal schemas that we can ETL the data into. We then use an on-prem SQL Server to execute our SSIS packages, which support a DSN connection.
So far it's been very easy and very successful.
So far it's been very easy and very successful.
- Processing speed
- Scaling warehouses
- Ease of use
- Hard to say, they're adding new features all the time.
- I feel like Snowflake's documentation is a little too thorough, it can be hard to understand
- I'm not a fan of the web interface, I use DBeaver instead.
Snowflake is giving a very robust cloud-based data warehousing solution with all the benefits of going to the cloud. Data sharing is one critical area in data management and Snowflake's innovative way of sharing data without physically moving it as a great feature. This is the exact needs that many of my clients had and Snowflake was just about a perfect fit!
- Data sharing without physically moving data and without compromising security aspect
- Unlimited scalability and elasticity (with proven client examples)
- Almost no to very little maintenance (Snowflake takes care of it for you)
- Graphical user interface for developers to build their applications
- In-built CI-CD integration capabilities
- In-built data lineage capabilities
January 17, 2022
Cloud-based Data Warehouse solution provided as a Saas.
Snowflake is being used as a could based data warehousing solution. We are building a data lake using Snowflake and other tools such as HVR and Dell Boomi. Currently, we are having different solutions used by different business teams for reporting and analytics purposes. Now we are building a centralized solution for the entire organization.
- Cloud-based Data warehousing
- Very fast data processing and Analytics
- easy to learn and work
- limitation with unstructured data
- while importing data from other sources only bulk load
August 10, 2021
Snowflake the MPP data platform of the future, today!
Snowflake is used as a scale-out data lake and data warehouse at Spireon. The separation of compute from storage enables the company to provide timely and scalable insights. The confluence of streaming and batch processing at a pay-as-you-go pricing model aids in being intelligent and efficient on budget planning and use.
- Massive parallel processing
- SQL for schema-on-read data lakes
- Secure and compressed storage for semi-structured data
- Support site
- Transparency on performance
- Full text search
Snowflake is used as the central data warehouse for data coming from all divisions of the College. Once in Snowflake, we use a variety of business intelligence tools to pull the data and do reporting and analysis. It also allows us to spend as we grow our data needs, rather than spending a huge up-front investment.
- Efficient handling of large data sets in a scalable way
- Ability to connect from a variety of tools (Tableau, Metabase, JDBC, many more)
- Querying and output of data in JSON format
- Built-in query and export tools
- Security roles and access are hard to understand and manage
- Rollout of new features seems to heavily favor US West coast, everyone else has to wait
- Visual interface does not allow you to manage custom functions and routines. For those, it is code only. Management of tables and views is visual.
Snowflake has enabled me to connect with data service providers. Through this software, I am capable of making data-driven decisions and providing my customers modern and integrated data applications. It is a cost-effective tool and we are its satisfied customers. This software has occupied every nook and corner of my IT department and we are at ease to handle the online data and supply it to our customers.
- This is a cloud-based application that provides me a secure platform for the easy sharing of data with my clients.
- I feel confident to connect with my numerous business partners just because of its advanced security and effective programming.
- Through this tool, I am capable of integrating, analyzing, and the entire data in a precise form and with analytics as well, due to which I always have a transparent idea about the data extraction and its transfer from multiple clouds.
- This tool is very much technical and proper knowledge is required, so mostly you have to hire an IT team.
- I wish if various videos could be available for basic quires like its initiation, then I think it would act as a guideline and would help the beginners a lot.
January 04, 2021
Snowflake has worked Great in our company!
Snowflake is being used across all departments of the company. It's our main data warehouse and system of record for sales, inventory and other metrics of the company. Snowflake helps us address different business questions from executives and help them make decisions based on the different metrics being analyzed.
- Snowflake computes really fast and can handle high volumes of data with ease.
- Snowflake has some features that have really helped DBAs and developers particularly with Time Travel, it has help us with many processes in our company where we had to rollback or re-apply sweep processes which would be time consuming.
- Snowflake has forced ETL developers to write better code (forcing ANSI standards) and avoided implicit conversions in specific data-types for different subject areas.
- Loading processes have improved. Prior to Snowflake, some ETL processes would take double the time to execute. With Snowflake those same processes finish in half the time.
- Integration with other tools, particularly with connectivity. We have observed metadata callbacks being generated which are time consuming and annoying. These can be avoided but extra work is required.
- Out of the box tools could be better. Specifically the querying tool is lacking a few features that other software offer for easy of use for users and developers.
- Not really a Con, but in Snowflake there's no concept for Indexes, maybe because they are not required but we have seen particular cases where we believe an index would help speed some of the queries being executed.
December 28, 2020
Snowflake is a future full stack database
Snowflake is acting as a company-wide Data Repository. With its cloud architecture and scalability, it addresses our storage, warehouse, and computation problem at the same time. Snowflake has powerful group roles and policy, which makes it beneficial for enterprise edition and usage. The ability to change the computational resources anytime is one of the biggest advantages. We have from manager to analyst been consuming the Snowflakes as a data repo. We have around a few hundred TB of data stored and it works smoothly on data growing exponentially too.
- Hosted on cloud: Helps with scalability.
- Community is active and ever-growing: You will have someone from the community to help whenever you need it.
- The new functionality and thoughtful design are based on new world problems.
- Support for JSON and XML is one of the main advantages.
- Beta testing functionality needs to be properly tested and stick to the committed deadline set at the initial release.
- The ODBC connector could be improved to accommodate multiple roles.
- Updates on functionality need to be informed to the user. Just a document update might not be the right approach every time.
November 25, 2019
Amazing cloud-based DB
We use Snowflake on our Data Engineering team to house our data warehouse and offload a substantial amount of our ETL processes to Snowflake. Snowflake enables us to offer ultra-fast querying to the business to quickly gain insights into our current data set.
- Extremely intuitive and easy to use querying language.
- Allows high performance querying of large data sets with very little setup and configuration.
- Interfaces very easily with AWS S3.
- Works seamlessly with both structured and unstructured data sets.
- Very granular security.
- IDE is OK but can be a bit clunky given it's web-based.
November 20, 2019
A vast improvement to the cloud!
Snowflake is being used on top of our Azure data warehouse. It solves our issue of queries running at the same time and has drastically improved our server performance. All of our reports connect to Snowflake and they all run very fast. It is currently being used across the entire company.
- You are able to adjust the power that you give a query. For the big queries, you can give more CPU to it so it runs faster.
- It can now sit on Google Cloud, S3, and Azure.
- Concurrency is a thing of the past.
- I'd love to see a desktop tool for Snowflake. Currently, it is all web-based.
- Database navigation can be smoother. It's not as efficient as a SQL workbench.
- Row-level security is possible, but it was difficult to figure out.
June 10, 2019
Snowflake's ease of use allows you to focus on what matters most - the data you're filling it with
My company adopted Snowflake as our first cloud-based data warehouse. It is being used as a central repository for all company data from each business unit for the purposes of business intelligence.
- Ease of use
- Separation of storage and compute resources
- Simple to scale up or down with virtual warehouses
- Built-in support for the most popular data formats
- Standard SQL dialect
- Robust function library
- Lacks support for common table expressions
- Lacks support for correlated subqueries
- Better technical support for customer identified bugs
- Clearer pricing model
May 21, 2019
Snowflake Performance for Large Company
We are using Snowflake as our data warehouse. We currently are loading in our tables and data from an old IBM System to Snowflake. It is currently being used by a few departments but is planning to be used across the whole organization.
- Performance is extremely fast
- Pay for what you use
- Simple and Pleasant User Interface
- The mouse pointer can be laggy at times when hovering over a preview of a table
- Make it easier to switch between data warehouses
It is used by Data teams across different departments of the company for compute purposes.
- On demand and instant spin up of compute instances is fantastic
- I like the browser based tabs which save queries
- Easy connection to Python and BI tools
- SQL editor can be better with autocomplete functions
Snowflake is being used across our whole organization. It addresses the need to combine disparate data sources into one single data source and discover insights into our business that would not be easily possible with lots of disconnected data sources. It also delivers world-class query performance and the ability for different business divisions to query their own data quickly and create reports in a fraction of the time as opposed to a traditional data warehouse solution. We are also using it to drive machine learning, and the data scientists are gaining insights into our business data that would not be possible otherwise. It is addressing multiple business problems, from distribution of our products all the way through to billing.
- Reporting queries run in a fraction of the time that they would in our production systems. For example, we can take the original MS SQL reporting queries , that used to take hours to run in our OLTP databases, and convert it into snow SQL, and run almost the exact same query in Snowflake in minutes, if not seconds.
- Having all our different data sources in one data warehouse database means we can start looking for links between data sources and different business units to tie all our data together. We can see from when a customer was dialled, through to when/if they bought a product, to when they were actually billed, and identify where in the process we are most efficient, and where we can improve our services and product offerings.
- Having a truly automated database system, without the need to create indices or maintain them, means we can spend more time in gaining insights into our data and getting actual results/data out, rather than spending time managing and maintaining the solution.
- There is no easy way to schedule any type of task.
May 05, 2019
Cloud-Based Data Warehousing Done Right
We replaced our RDS Postgres based DW with Snowflake. We use it as the main data source for all analytics components within our SaaS product, internal reporting, and ad hoc analysis by power users. We are now also able to analyze JSON without the need for transformation by easily replicating S3 buckets with Snowpipe.
- Provision compute resources instantly and autoscaling. True elastic, pay as you go pricing model.
- Secure Data Sharing. No other vendor offers this. This is big if you have the need to do a lot of data extracts.
- Ability to segregate clusters of computer resources (warehouses) by use pool. You can give power users access without the fear of slowing down critical applications.
- Cloud first architecture offers simple integration with other cloud-centric technologies/tools like S3 storage, streaming/replication brokers like Kafka, Alooma and cloud base BI tools.
- Big Data analytics capabilities with the familiarity of ANSI SQL. Short learning curve.
- Compilation times on somewhat complex queries is high. We use materialized views to address this problem and take advantage of caching, but we believe there is room for improvement here.
- SLA's dependent on the big cloud player (AWS, Azure, GCP). If they have interruptions, you have interruptions. This is the current reality of cloud computing.
April 25, 2019
The best data warehouse on the market
We use Snowflake across our entire organization. We selected Snowflake to replace Redshift as our data warehouse. All of our data now funnels into Snowflake and users are able to query it and draw insights that they have never had before. Additionally, we were able to build and release a reporting dashboard for our external clients to see all of their historical data with us in one place.
- You only pay for the resources when you are using them
- ANSI SQL compliant
- Great documentation
- Native Apache Spark connector
- Does not support Dynamic SQL
- Right now you can write User-Defined Functions (UDFs) in pure SQL or Javascript. I would love to see support for something like Python
- We have been seeing more downtime lately as of writing this review
August 06, 2018
Snowflake - a very cost effective JSON querying tool.
Snowflake is currently being used to ingest daily JSON files exported from an analytics package into S3. We use Snowflake for Ad Hoc Queries, aggregating daily KPIs and pushing that data into a SQL Server, as well as creating Tableau extracts for our dashboards. We have also started using it for deeper Machine Learning types of analysis - such as creating predictive models.
- Process Engine control - we can stop/pause/start engines for various tasks.
- Processing speed is adequate unless there are many users on at the same time.
- Web interface is easy and intuitive, like the fact that your queries are automatically saved in tabs.
- Very limited amount of tabs - saved queries, which requires us to store the code somewhere else and re-use existing queries.
- Performance can really be a problem if there are many users on the system at the same time.
- SnowFlake support sometimes can be hard to reach.
October 11, 2017
Your DWH entirely on the cloud!
The analytics and reporting team uses Snowflake as their primary Business Intelligence (BI) tool. Combined with several reporting and charting tools, Snowflake provides insight across all departments in the organisation. Snowflake helps provide the business with crucial analytical understanding of performance which, in turn, influences business strategy for the entire organisation.
- Easy to set up and get running.
- Great support.
- Integrates well with Amazon AWS.
- Charting features could be better.
- Reporting tools are not very extensive, creating a need for combining with other tools like Tableau.
- Data Warehouse entirely on the cloud might be a problem for some businesses.