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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 users experience mixed ROI; challenges in calculation exist, but long-term benefits include cost reduction and improved data management.
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 helpfulness, though some note delays and lack of SLAs.
Whenever we reach out, they respond promptly.
As of now, we are raising issues and they are providing solutions without any problems.
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 is praised for scalability and efficiency, but concerns exist regarding cost-effectiveness in medium to large-scale organizations.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
Databricks is an easily scalable platform.
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
7.6
Databricks is stable and efficient for large data, with minor issues during updates and occasional connectivity challenges.
Sentiment score
8.2
Snowflake is praised for stability and reliability, with users noting excellent performance, quick issue resolution, and robust architecture.
Although it is too early to definitively state the platform's stability, we have not encountered any issues so far.
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 seek improved UI, pricing transparency, analytics, integrations, AI features, and enhanced support, ETL, and machine learning capabilities.
We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.
This feature, if made publicly available, may act as a game-changer, considering many global organizations use SAP data for their ERP requirements.
We could use their job clusters, however, that increases costs, which is challenging for us as a startup.
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 offers flexibility but can be unpredictable and expensive compared to Redshift or BigQuery, with room for transparency improvements.
It is not a cheap solution.
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 excels in scalable, secure data processing with fast queries, multi-format support, and seamless third-party integration for AI/ML.
Databricks' capability to process data in parallel enhances data processing speed.
The platform allows us to leverage cloud advantages effectively, enhancing our AI and ML projects.
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.
Being able to perform AI and Machine Learning in the same location as the data is quite advantageous.
 

Categories and Ranking

Databricks
Ranking in Cloud Data Warehouse
7th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
89
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 May 2025, in the Cloud Data Warehouse category, the mindshare of Databricks is 8.8%, up from 3.7% compared to the previous year. The mindshare of Snowflake is 19.6%, down from 22.9% 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
18%
Computer Software Company
10%
Manufacturing Company
9%
Healthcare Company
6%
Educational Organization
35%
Financial Services Firm
13%
Computer Software Company
9%
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: April 2025.
850,028 professionals have used our research since 2012.