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Snowflake pros and cons

Vendor: Snowflake Computing

4.2 out of 5

99 reviews
97% willing to recommend

2,058 followers

Pros & Cons summary

Snowflake offers remarkable scalability with its distributed architecture, allowing independent scaling of compute and storage. Features like data sharing, Time Travel, and Zero Copy Cloning boost performance, while the separation of storage and compute facilitates cost-effective pricing. Integration with various data sources furthers its cloud data warehousing capabilities. However, Snowflake requires improvements in spatial capabilities, support services, and migration processes to enhance its effectiveness and address pricing transparency issues for tech buyers.

Buyer's Guide

Get pricing advice, tips, use cases and valuable features from real users of this product.

Prominent pros & cons

PROS

Snowflake's distributed architecture enables rapid processing of extensive datasets and offers scalability by allowing independent scaling of compute and storage.

This database platform excels in data sharing capabilities, facilitating easy access and collaboration across multiple teams and sources.

Its performance in query execution is notably fast, leveraging the cloud's power for efficient data processing and transformation tasks.

Snowflake provides seamless integration capabilities for varied data sources and analytic applications, enhancing overall data management and processing efficiency.

Data and memory management in Snowflake is highly automated, minimizing maintenance requirements and enabling hassle-free management of both structured and unstructured data.

CONS

Snowflake needs improvement in its spatial capabilities, lacking robust geo-spatial query support.

Improvements in stored procedures and more robust SQL language compatibility, particularly for easier migration from other databases, are necessary.

Snowflake should enhance its data integration and ETL functionalities to reduce reliance on third-party tools.

The need for an on-premises version with similar features to the cloud option is noted by some users.

There are concerns about the pricing strategy and cost transparency associated with using Snowflake.

Snowflake Pros review quotes

reviewer1614864

Center Head - Goa Regional Delivery Center. at a tech services company with 51-200 employees

Sep 10, 2024

I don't think it is difficult to maintain.

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Vice President of Business Intelligence and Data Engineering at a comms service provider with 201-500 employees

Dec 12, 2019

The thing I find most valuable is that scalability, space storage, and computing power is separate. When you scale up, it is live from one second to the next — constantly available as you scale — so there is no downtime or interruption of services.

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SR

SreenivasanRamanujam

Director -Data Architecture and Engineering at Decision Minds

Feb 23, 2021

Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning 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.

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Sr Manager at Cognizant

May 12, 2022

Time travel is one feature that really helps us out.

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Data Lead at InterWorks

Apr 27, 2023

It is a highly scalable solution. There is no limit on storage or computing.

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director of business operations at a logistics company with 51-200 employees

Nov 7, 2021

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.

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reviewer1553778

Solution Architect at a wholesaler/distributor with 10,001+ employees

Apr 17, 2021

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.

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Anirban Bhattacharya

Practice Head, Data & Analytics at Tech Mahindra Limited

Apr 9, 2021

The way it is built and designed is valuable. The way the shared model is built and the way it exploits the power of the cloud is very good. Certain features related to administration and management, akin to Oracle Flashback and all that, are very important for modern-day administration and management. It is also good in terms of managing and improving performance, indexing, and partitioning. It is sort of completely automated. Everything is essentially under the hood, and the engine takes care of it all. As a data warehouse on the cloud, Snowflake stands strong on its ground even though each of the cloud providers has its own data warehouse, such as Redshift for AWS or Synapse for Azure.

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HB

Hemant Balijepalli

Senior Consultant at Deloitte

Nov 9, 2022

The solution is stable.

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MR

Mauricio Ruiz Falcón

Senior Information Management Architect at Raken

Jan 24, 2021

The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also.

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Snowflake Cons review quotes

reviewer1614864

Center Head - Goa Regional Delivery Center. at a tech services company with 51-200 employees

Sep 10, 2024

From an improvement perspective, Snowflake can evolve in terms of writing costly, expensive queries with less cost and try to see if pipeline development can be made a little easier.

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Vice President of Business Intelligence and Data Engineering at a comms service provider with 201-500 employees

Dec 12, 2019

Maybe there could be some more connectors to other systems, but this is what they are constantly developing anyway.

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SR

SreenivasanRamanujam

Director -Data Architecture and Engineering at Decision Minds

Feb 23, 2021

Portability is a big hurdle right now for our clients. Porting all of your existing SQL ecosystem, such as stored procedures, to Snowflake is a major pain point. Currently, Snowflake stored procedures use JavaScript, but they should support SQL-based stored procedures. It would be a huge advantage if you can write your stored procedures using SQL. It seems that they are working on this feature, and they are yet to release it. I remember seeing some notes saying that they were going to do that in the future, but the sooner this feature comes out, it would be better for Snowflake because there are a lot of clients with whom I'm interacting, and their main hurdle is to take their existing Oracle or SQL Server stored procedures and move them into Snowflake. For this, you need to learn JavaScript and how it works, which is not easy and becomes a little tricky. If it supports SQL-based procedures, then you can just cut-paste the SQL code, run it, and easily fix small issues.

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Sr Manager at Cognizant

May 12, 2022

The solution could use a little bit more UI.

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Data Lead at InterWorks

Apr 27, 2023

Sometimes it can be tricky to manage multiple environments if you're purely using Snowflake as your scripting and pipeline environment.

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reviewer1553778

Solution Architect at a wholesaler/distributor with 10,001+ employees

Apr 17, 2021

They need to incorporate some basic OLAP capabilities in the backend or at the database level. Currently, it is purely a database. They call it purely a data warehouse for the cloud. Currently, just like any database, we have to calculate all the KPIs in the front-end tools. The same KPIs again need to be calculated in Snowflake. It would be very helpful if they can include some OLAP features. This will bring efficiency because we will be able to create the KPIs within Snowflake itself and then publish them to multiple front-end tools. We won't have to recreate the same in each project. There should be the ability to automate raised queries, which is currently not possible. There should also be something for Exception Aggregation and things like that.

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director of business operations at a logistics company with 51-200 employees

Nov 7, 2021

An additional feature I'd like to see is called materialized views, which can speed up some run times. I'd like it to be able to be used where you can have multiple tables inside them; materialized view. That would be nice. As well as being able to run cursors, to be able to do some bulk updates and some more advanced querying, table building on the fly.

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Anirban Bhattacharya

Practice Head, Data & Analytics at Tech Mahindra Limited

Apr 9, 2021

There are three things that came to my notice. I am not very sure whether they have already done it. The first one is very specific to the virtual data warehouse. Snowflake might want to offer industry-specific models for the data warehouse. Snowflake is a very strong product with credit. For a typical retail industry, such as the pharma industry, if it can get into the functional space as well, it will be a big shot in their arm. The second thing is related to the migration from other data warehouses to Snowflake. They can make the migration a little bit more seamless and easy. It should be compatible, well-structured, and well-governed. Many enterprises have huge impetus and urgency to move to Snowflake from their existing data warehouse, so, naturally, this is an area that is critical. The third thing is related to the capability of dealing with relational and dimensional structures. It is not that friendly with relational structures. Snowflake is more friendly with the dimensional structure or the data masks, which is characteristic of a Kimball model. It is very difficult to be savvy and friendly with both structures because these structures are different and address different kinds of needs. One is manipulation-heavy, and the other one is read-heavy or analysis-heavy. One is for heavy or frequent changes and amendments, and the other one is for frequent reads. One is flat, and the other one is distributed. There are fundamental differences between these two structures. If I were to consider Snowflake as a silver bullet, it should be equally savvy on both ends, which I don't think is the case. Maybe the product has grown and scaled up from where it was.

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HB

Hemant Balijepalli

Senior Consultant at Deloitte

Nov 9, 2022

I don't know about GCP, if they have connected for GCP. If they don't, they should allow for it.

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MR

Mauricio Ruiz Falcón

Senior Information Management Architect at Raken

Jan 24, 2021

It would benefit from an administration that allows you to be aware of your credit consumption once you have the service so that you may be sure how many credits you are consuming when you use the platform and to make sure that you are making the most efficient use of these resources. In other words, to improve their interface so that you may monitor the consumption of your credits on Cloud.

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Product Categories

Product Categories

Cloud Data Warehouse

AI Synthetic Data

Popular Comparisons

Popular Comparisons

Azure Data Factory vs Snowflake

Teradata vs Snowflake

Microsoft Azure Synapse Analytics vs Snowflake

Vertica vs Snowflake

Amazon Redshift vs Snowflake

Dremio vs Snowflake

BigQuery vs Snowflake

Amazon EMR vs Snowflake

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