Feb 02, 2022
handling of semi-structured data like json. It has great support for json and we can write sql on json which is amazing. the performance on semi-structured data is little poor as compared to structured data but it is still great.
Snowflake and Snowflake Analytics compete in the cloud data platform category. Snowflake appears to have the upper hand due to its broader technical feature set, while Snowflake Analytics is more suited for business-focused ready-to-use analytics solutions.
Features: Snowflake offers scalability, flexibility, and advanced analytics capabilities, effectively handling large datasets and supporting various file formats. It allows for virtual warehouse resizing and zero-copy cloning, facilitating development and testing environments. Snowflake Analytics provides intuitive data exploration tools and customizable dashboards, enhancing business-focused analytics with ease of use and interaction.
Room for Improvement: Snowflake could improve its geo-spatial capabilities, streamline Snowpipe auto-ingestion, and provide clearer pricing models. Enhancements in the interface and stored procedure support are also necessary. Snowflake Analytics would benefit from better machine learning integration, more interactive UI elements, and stronger transactional processing support, alongside improved pipeline creation and cost transparency.
Ease of Deployment and Customer Service: Both Snowflake and Snowflake Analytics leverage public cloud environments, while Snowflake extends support to private and hybrid clouds, offering greater flexibility. Customer service for both is generally efficient, but Snowflake integrates support directly into its UI, providing immediate access for problem-solving.
Pricing and ROI: Snowflake uses a pay-as-you-go model praised for flexibility but requires careful management to avoid high costs. Snowflake Analytics also opts for usage-based pricing, which can be seen as expensive. Both promise significant ROI through enhanced operational efficiencies and data management, though affordability may vary based on specific use cases.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
Snowflake is very scalable and has a dedicated team constantly improving the product.
Storage is unlimited because they use S3 if it is AWS, so storage has no limit.
Snowflake is very stable, especially when used with AWS.
Cost reduction is one area I would like Snowflake to improve.
AIML-based SQL prompt and query generation could be an area for enhancement.
Navigating the user console can be challenging, particularly when looking for details like the account ID.
Snowflake's pricing is on the higher side.
Snowflake is better and cheaper than Redshift and other cloud warehousing systems.
Snowflake charges per query, which amounts to a very minor cost, such as $0.015 per query.
One key feature is the separation of compute and storage, which eliminates storage limitations.
Running a considerable query on Microsoft SQL Server may take up to thirty minutes or an hour, while Snowflake executes the same query in less than three minutes.
It is a data offering where I can see data lineage, data governance, and data security.
Snowflake is a cloud-based data warehousing solution for storing and processing data, generating reports and dashboards, and as a BI reporting source. It is used for optimizing costs and using financial data, as well as for migrating data from on-premises to the cloud. The solution is often used as a centralized data warehouse, combining data from multiple sources.
Snowflake has helped organizations improve query performance, store and process JSON and XML, consolidate multiple databases into one unified table, power company-wide dashboards, increase productivity, reduce processing time, and have easy maintenance with good technical support.
Its platform is made up of three components:
Snowflake has many valuable vital features. Some of the most useful ones include:
There are many benefits to implementing Snowflake. It helps optimize costs, reduce downtime, improve operational efficiency, and automate data replication for fast recovery, and it is built for high reliability and availability.
Below are quotes from interviews we conducted with users currently using the Snowflake solution:
Sreenivasan R., Director of Data Architecture and Engineering at Decision Minds, says, "Data sharing is a good feature. It is a majorly used feature. The elastic computing is another big feature. Separating computing and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not doing any performance tuning, and the entire burden of performance and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."
A director of business operations at a logistics company mentions, "It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well."
A Solution Architect at a wholesaler/distributor comments, "The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."
Conventional data platforms and big data solutions struggle to deliver on their fundamental purpose: to enable any user to work with any data, without limits on scale, performance or flexibility. Whether you’re a data analyst, data scientist, data engineer, or any other business or technology professional, you’ll get more from your data with Snowflake.
To achieve this, we built a new data platform from the ground up for the cloud. It’s designed with a patented new architecture to be the centerpiece for data pipelines, data warehousing, data lakes, data application development, and for building data exchanges to easily and securely share governed data. The result, A platform delivered as a service that’s powerful but simple to use.
Snowflake’s cloud data platform supports a multi-cloud strategy, including a cross-cloud approach to mix and match clouds as you see fit. Snowflake delivers advantages such as global data replication, which means you can move your data to any cloud in any region, without having to re-code your applications or learn new skills.
We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
