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AWS Lake Formation vs Snowflake comparison

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Comparison Buyer's Guide
Executive Summary

We performed a comparison between AWS Lake Formation and Snowflake based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed AWS Lake Formation vs. Snowflake report (Updated: August 2022).
634,590 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The most important advantage in using AWS Lake Formation is its ability to connect the data lake to the other technologies in AWS. This is what I advise my clients.""The solution is quite good at handling analytics. It's done a good job at helping us centralize them."

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"The initial setup is very simple.""It was relatively easy to use, and it was easy for people to convert to it.""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.""The overall ecosystem was easy to manage. Given that we weren't a very highly technical group, it was preferable to other things we looked at because it could do all of the cloud tunings. It can tune your data warehouse to an appropriate size for controlled billing, resume and sleep functions, and all such things. It was much more simple than doing native Azure or AWS development. It was stable, and their support was also perfect. It was also very easy to deploy. It was one of those rare times where they did exactly what they said they could do.""It is a very well-distributed system. It has different data engines for different applications. Many applications can use different computational engines at the same time. In terms of data processing, the feeling was similar to working with a relational database but in a scalable way.""It is a very easy-to-use solution. It is user-friendly, and its setup time is very less.""The adaptation to development languages is most valuable. Our developers can SQL code or something else. It has been convenient in that regard.""Time travel is one feature that really helps us out."

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Cons
"For the end-users, it's not as user-friendly as it could be.""In our experience what could be improved are not the support, performance or monitoring, but at a managerial level, the very expensive professional services of AWS. This could be an area of improvement for them. It's too expensive to acquire their support."

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"Some SQL language functions could be included.""I would like to see more transparency in data processing, ATLs, and compute areas - which should give more comfort to the end users.""These aren't as crucial, but there are common errors sometimes where the database is down, or a table is nullified and a new table is added and you are not given access to that. With those errors, you don't have permissions.""It would be better if they had a data profile tool that tells me where the gaps are in my time series data.""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.""The solution could use a little bit more UI.""The solution needs more connectors.""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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Pricing and Cost Advice
Information Not Available
  • "On average, with the number of queries that we run, we pay approximately $200 USD per month."
  • "Pricing is approximately $US 50 per DB. Terabyte is around $US 50 per month."
  • "The price of Snowflake is very reasonable."
  • "The price of Snowflake is quite reasonable."
  • "Its price should be improved. It should be cheaper than Microsoft."
  • "It is per credit. It has a use-it-as-you-go model. We bought a chunk of 20,000 credits, and they were lasting us for at least a year. We didn't have the scale of data like a much larger company to consume more credits. For us, it was very inexpensive. Their strategy is just to leverage what you've got and put Snowflake in the middle. It doesn't make it expensive because most of the organizations already have reporting tools. Now, if you were starting from scratch, it might be cheaper to go a different way."
  • "We used Snowflake to see if it is cheaper than using BigQuery. It was just to maintain the cost or the KPI regarding the cost of connectivity by users. Snowflake wasn't cheaper than BigQuery, and its affordability was the main issue."
  • "Currently, we have a trial account, so we don't need a license. After our project starts, we would need a permanent license."
  • More Snowflake Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:The solution is quite good at handling analytics. It's done a good job at helping us centralize them.
    Top Answer:I'm not privvy to licesning information. I'm not sure how much the solution costs.
    Top Answer:We occasionally work with third-party libraries and they fail to integrate with this product effectively. For the end-users, it's not as user-friendly as it could be. For example, if I have a Lake… more »
    Top Answer:The most valuable feature is the clone copy.
    Top Answer:They have different pricing structures based on data usage. I think they have three or four tiers you can scale through. Most of the clients see an advantage from this type of licensing. That's the… more »
    Top Answer:In a future release we would like to have a link which would allow us to connect to an external database and create certain views in your own database. This is because it is becoming hard for us to… more »
    Ranking
    11th
    Views
    4,031
    Comparisons
    3,024
    Reviews
    2
    Average Words per Review
    655
    Rating
    8.0
    1st
    Views
    39,465
    Comparisons
    28,761
    Reviews
    49
    Average Words per Review
    550
    Rating
    8.4
    Comparisons
    Also Known As
    Snowflake Computing
    Learn More
    Overview

    AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis.

    Snowflake is a fully managed SaaS (software as a service) that provides a single platform for data warehousing, data lakes, data engineering, data science, data application development, and secure sharing and consumption of real-time / shared data.

    Its platform is made up of three components:

    1. Cloud services: As part of its cloud services, Snowflake uses ANSI SQL, which empowers users to optimize their data and manage their infrastructure, while Snowflake handles the security and encryption of stored data.
    1. Query processing: With Snowflake, workload concurrency is never a problem because its compute layer is made up of virtual cloud data warehouses that let you analyze data through requests. Each of the warehouses do not compete for computing resources nor do they affect the performance of each other.
    1. Database storage: Snowflake manages all parts of the data storage process automatically, including file size, compression, organization, structure, and metadata, as well as statistics.

    Snowflake Features

    Snowflake has many valuable key features. Some of the most useful ones include:

    • Scalability: Snowflake architecture provides nearly unlimited scalability and high speed because it uses a single elastic performance engine. The solution also supports an unlimited amount of concurrent users and workloads, from interactive to batch.
    • Automation: Snowflake makes automation easy and enables enterprises to automate data management, security, governance, availability, and data resiliency.
    • Seamless cross-cloud and cross-region connections: With seamless cross-cloud and cross-region connections, Snowflake eliminates ETL and data silos. Anyone who needs access to shared secure data can get a single copy via the data cloud. In addition, Snowflake makes remote collaboration and decision-making fast and easy via a single shared data source.
    • Third-party data integrations: Snowflake’s Data Marketplace offers third-party data which allows you to connect with Snowflake customers to extend workflows with data services and third-party applications.

    Snowflake Benefits

    There are many benefits to implementing Snowflake. Some of the biggest advantages the solution offers include:

    • Helps optimize costs
    • Reduces downtime
    • Improves operational efficiency
    • Built for high reliability and availability
    • Automates data replication for fast recovery

    Reviews from Real Users

    Below are some reviews and helpful feedback written by PeerSpot 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 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."

    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."

    Offer
    Learn more about AWS Lake Formation
    Learn more about Snowflake
    Sample Customers
    bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
    Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm17%
    Computer Software Company15%
    Media Company7%
    Comms Service Provider7%
    REVIEWERS
    Computer Software Company36%
    Financial Services Firm12%
    Manufacturing Company9%
    Comms Service Provider6%
    VISITORS READING REVIEWS
    Computer Software Company19%
    Financial Services Firm12%
    Comms Service Provider10%
    Insurance Company6%
    Company Size
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise11%
    Large Enterprise74%
    REVIEWERS
    Small Business23%
    Midsize Enterprise22%
    Large Enterprise55%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise13%
    Large Enterprise70%
    Buyer's Guide
    AWS Lake Formation vs. Snowflake
    August 2022
    Find out what your peers are saying about AWS Lake Formation vs. Snowflake and other solutions. Updated: August 2022.
    634,590 professionals have used our research since 2012.

    AWS Lake Formation is ranked 11th in Cloud Data Warehouse with 2 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 49 reviews. AWS Lake Formation is rated 8.0, while Snowflake is rated 8.4. The top reviewer of AWS Lake Formation writes "Stable and good at handling analytics but needs to better accept integrations". On the other hand, the top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". AWS Lake Formation is most compared with Microsoft Azure Synapse Analytics, Amazon Redshift, Azure Data Factory, Amazon EMR and Apache Hadoop, whereas Snowflake is most compared with Microsoft Azure Synapse Analytics, Amazon Redshift, Vertica, Teradata and Azure Data Factory. See our AWS Lake Formation vs. Snowflake report.

    See our list of best Cloud Data Warehouse vendors.

    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.