AWS Lake Formation vs Databricks comparison

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AWS Lake Formation

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Executive Summary

We performed a comparison between AWS Lake Formation and Databricks 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. Databricks Report (Updated: March 2025).

AWS Lake Formation vs. Databricks

March 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

AWS Lake Formation

Ranking in Cloud Data Warehouse

13th

Average Rating

7.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Databricks

Ranking in Cloud Data Warehouse

7th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Data Science Platforms (1st), Streaming Analytics (1st)

Mindshare comparison

As of April 2025, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 5.2%, down from 6.0% compared to the previous year. The mindshare of Databricks is 8.4%, up from 3.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse

Featured Reviews

Ramesh Raghavan

US South Lead, Accenture AWS Business Group at Accenture

Centralized repository, offers various cataloging mechanisms for quick data retrieval but data governance capabilities could be better

There are a couple of areas for improvement with Lake Formation. One of the main challenges, especially when dealing with rich media content, like in MarTech (Marketing Technology) or ad agencies, is its versatility. Some clients feel that Lake Formation doesn’t meet their needs and they tend to prefer competitor products for those specific use cases. The second area for improvement is in data governance. Specifically, Lake Formation could enhance its capabilities in audit logs, real-time monitoring, and advanced data governance. This includes managing the entire data lineage—where the data originated, how it moves, and where it’s currently stored. The visibility of the data as it evolves is crucial, and that’s where more advanced governance capabilities would be beneficial.

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ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

Capability to integrate diverse coding languages in a single notebook greatly enhances workflow

Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The solution has many features that are applicable to events such as audits."

"AWS Lake Formation lets you see all your data and tables on one screen."

"I can easily move data from cold storage to regular storage."

"It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services."

"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."

"AWS Lake Formation works hand in hand with other products."

"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."

"We use AWS Lake Formation typically for the data warehouse."

"Databricks serves as a single platform for conducting the entire end-to-end lifecycle of machine learning models or AI ops."

"It's very simple to use Databricks Apache Spark."

"Databricks has improved my organization by allowing us to transform data from sources to a different format and feed that to the analytics, business intelligence, and reporting teams. This tool makes it easy to do those kinds of things."

"The main features of the solution are efficiency."

"Databricks' capability to process data in parallel enhances data processing speed."

"The integration with Python and the notebooks really helps."

"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."

"The most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."

More Databricks pros

Cons

"AWS Lake Formation's pricing could be cheaper."

"You need to have data experience to use the product."

"The solution could make improvements around orchestration and doing some automation stuff on AWS front automation. It would be useful if we could use automation to build images and use hardened images which are CIS compliant."

"It falls short when it comes to more granular access control, such as cell-level or row-level entitlements which is a significant drawback for organizations that require precise control over who can access specific rows of data."

"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."

"Lake Formation could enhance its capabilities in audit logs, real-time monitoring, and advanced data governance."

"If I could improve AWS Lake Formation, I would add more integrations with SageMaker."

"For the end-users, it's not as user-friendly as it could be."

"Cluster failure is one of the biggest weaknesses I notice in our Databricks."

"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."

"The product cannot be integrated with a popular coding IDE."

"The integration and query capabilities can be improved."

"There would also be benefits if more options were available for workers, or the clusters of the two points."

"The stability of the clusters or the instances of Databricks would be better if it was a much more stable environment. We've had issues with crashes."

"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."

"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."

More Databricks cons

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."

"The basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."

"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."

"The price of Databricks is reasonable compared to other solutions."

"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."

"Databricks' cost could be improved."

"Price-wise, I would rate Databricks a three out of five."

"I would rate Databricks' pricing seven out of ten."

"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."

More Databricks pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

21%

Computer Software Company

14%

Manufacturing Company

Government

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about AWS Lake Formation?

It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services.

What is your experience regarding pricing and costs for AWS Lake Formation?

The pricing is expensive compared to OpenStack, but cheaper than other cloud environments. It's middle-of-the-road for regular storage yet very cost-effective when using Amazon Glacier for data.

What needs improvement with AWS Lake Formation?

If I could improve AWS Lake Formation, I would add more integrations with SageMaker. I would have built-in functions that provide statistics for the data when using the GUI, such as SageMaker Insig...

Which do you prefer - Databricks or Azure Machine Learning Studio?

Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

Which would you choose - Databricks or Azure Stream Analytics?

Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...

Snowflake vs AWS Lake Formation

Comparisons

Compared 37% of the time

Amazon Redshift vs AWS Lake Formation

Compared 18% of the time

Azure Data Factory vs AWS Lake Formation

Compared 17% of the time

Microsoft Azure Synapse Analytics vs AWS Lake Formation

Compared 12% of the time

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Compared 11% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Dremio vs Databricks

Compared 8% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Tableau vs Databricks

Compared 5% of the time

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Product Reports

Download AWS Lake Formation product report

AWS Lake Formation

April 2025

Download Databricks product report

April 2025

Also Known As

No data available

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

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.

Amazon Web Services (AWS)

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware