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Databricks vs Snowflake comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 22, 2024

Review summaries and opinions

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

ROI

Sentiment score
6.6
Organizations experience mixed returns from Databricks, with benefits from cost savings and efficiency, but challenges in initial migration.
Sentiment score
6.8
Snowflake offers improved data management and security, with varied ROI perceptions, yet users recognize added value and efficiency.
When it comes to big data processing, I prefer Databricks over other solutions.
For a lot of different tasks, including machine learning, it is a nice solution.
 

Customer Service

Sentiment score
7.2
Databricks customer service is generally effective with prompt responses, though some report issues mainly with third-party support channels.
Sentiment score
7.3
Snowflake's customer service is praised for expertise and responsiveness, though some users experience delays due to time zone differences.
Whenever we reach out, they respond promptly.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
The technical support from Snowflake is very good, nice, and efficient.
 

Scalability Issues

Sentiment score
7.4
Databricks is praised for efficient scalability and cloud compatibility, allowing easy resource adjustment across diverse projects and industries.
Sentiment score
7.8
Snowflake offers seamless and cost-effective scalability with independent compute and storage, enabling efficient resource management for large data volumes.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
The billing doubles with size increase, but processing does not necessarily speed up accordingly.
Snowflake is very scalable and has a dedicated team constantly improving the product.
 

Stability Issues

Sentiment score
7.7
Databricks is stable and efficient for large data, with minor issues during updates and occasional connectivity challenges.
Sentiment score
8.2
Snowflake impresses users with remarkable stability, reliability, and performance, ensuring efficient data management with minimal disruptions and maintenance.
They release patches that sometimes break our code.
Cluster failure is one of the biggest weaknesses I notice in our Databricks.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
Snowflake is very stable, especially when used with AWS.
 

Room For Improvement

Databricks users desire improved UI, enhanced data visualization, better integration, clearer error messages, robust support, and comprehensive documentation.
Snowflake users desire improvements in spatial components, analytics, pricing, support, data protection, integration, and advanced AI features.
We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly.
If I could right-click to copy absolute paths or to read files directly into a data frame, it would standardize and simplify the process.
We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.
Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently require SQL coding, which might be challenging for some users.
Cost reduction is one area I would like Snowflake to improve.
 

Setup Cost

Databricks pricing depends on usage, with flexibility in licensing, and can vary in competitiveness compared to other solutions.
Snowflake's pricing is pay-as-you-go with competitive storage, higher compute costs, and discounts for bulk purchases, requiring usage optimization.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
 

Valuable Features

Databricks provides a unified platform for data engineering, machine learning, seamless cloud integration, and robust data management capabilities.
Snowflake is praised for its scalability, flexibility, performance, cost-effectiveness, and seamless integration with popular cloud platforms.
Databricks' capability to process data in parallel enhances data processing speed.
Developers can share their notebooks. Git and Azure DevOps integration on the Databricks side is also very helpful.
One key feature is the separation of compute and storage, which eliminates storage limitations.
The scalability options it provides, addressing issues without tying workloads into one virtual machine, enhance functionality.
 

Categories and Ranking

Databricks
Ranking in Cloud Data Warehouse
7th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
88
Ranking in other categories
Data Science Platforms (1st), Streaming Analytics (1st)
Snowflake
Ranking in Cloud Data Warehouse
1st
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
100
Ranking in other categories
Data Warehouse (1st), AI Synthetic Data (3rd)
 

Mindshare comparison

As of April 2025, in the Cloud Data Warehouse category, the mindshare of Databricks is 8.4%, up from 3.2% compared to the previous year. The mindshare of Snowflake is 20.5%, down from 22.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
 

Featured Reviews

ShubhamSharma7 - PeerSpot reviewer
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.
Snehasish Das - PeerSpot reviewer
Transformation in data querying speed with good migration capabilities
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses. One key feature is the separation of compute and storage, which eliminates storage limitations. It also has tools for migrating data from legacy databases like Oracle. Its stability and efficiency enhance performance greatly. Tools in the AI/ML marketplace are readily available without needing development.
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
10%
Manufacturing Company
9%
Healthcare Company
6%
Educational Organization
39%
Financial Services Firm
12%
Computer Software Company
8%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

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...
What do you like most about Snowflake?
The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power.
What is your experience regarding pricing and costs for Snowflake?
Snowflake's pricing is on the higher side, rated as eight out of ten. If there were ways to reduce costs, it would be a positive improvement.
What needs improvement with Snowflake?
Cost reduction is one area I would like Snowflake to improve. The product is not very cheap, and a reduction in costs would be appreciated.
 

Comparisons

 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
Snowflake Computing
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
Find out what your peers are saying about Databricks vs. Snowflake and other solutions. Updated: March 2025.
848,207 professionals have used our research since 2012.