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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
6.5
Databricks enhances efficiency and ROI, offering scalable solutions and cost savings over traditional Hadoop with easy setup.
Sentiment score
6.8
Snowflake users experience mixed ROI; challenges in calculation exist, but long-term benefits include cost reduction and improved data management.
For a lot of different tasks, including machine learning, it is a nice solution.
When it comes to big data processing, I prefer Databricks over other solutions.
 

Customer Service

Sentiment score
7.2
Databricks' support is generally praised for responsiveness, though some note delays, with resources often sufficient for independent problem-solving.
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 rate the technical support as fine because they have levels of technical support available, especially partners who get really good support from Databricks on new features.
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
7.5
Databricks is praised for its adaptability, scalability, automation features, and performance across industries but needs improved autoscaling control.
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.
I would rate the scalability of this solution as very high, about nine out of ten.
Snowflake is very scalable and has a dedicated team constantly improving the product.
The billing doubles with size increase, but processing does not necessarily speed up accordingly.
 

Stability Issues

Sentiment score
7.7
Databricks is highly rated for stability and performance, with occasional minor issues often due to user or external factors.
Sentiment score
8.2
Snowflake is praised for stability and reliability, with users noting excellent performance, quick issue resolution, and robust architecture.
They release patches that sometimes break our code.
Although it is too early to definitively state the platform's stability, we have not encountered any issues so far.
Databricks is definitely a very stable product and reliable.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
 

Room For Improvement

Databricks should improve visualization, integration, user experience, and scalability, addressing concerns about pricing, error messages, and onboarding.
Snowflake users seek improved UI, pricing transparency, analytics, integrations, AI features, and enhanced support, ETL, and machine learning capabilities.
Adjusting features like worker nodes and node utilization during cluster creation could mitigate these failures.
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.
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 offers flexible, often expensive pricing, mitigated by cloud deployment and tiered licensing, with varied user cost experiences.
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 offers an intuitive interface for data processing, integrating SQL, Python, and features like Delta Lake and MLflow.
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.
The Unity Catalog is for data governance, and the Delta Lake is to build the lakehouse.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
The independence of the compute and storage within Snowflake is key.
 

Categories and Ranking

Databricks
Ranking in Cloud Data Warehouse
8th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
91
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 (1st)
 

Mindshare comparison

As of June 2025, in the Cloud Data Warehouse category, the mindshare of Databricks is 8.9%, up from 4.1% compared to the previous year. The mindshare of Snowflake is 18.9%, down from 23.0% 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
19%
Financial Services Firm
17%
Computer Software Company
10%
Manufacturing Company
7%
 

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?
It is complicated to understand how requests impact warehouse size. Unlike competitors such as Microsoft and Databricks ( /products/databricks-reviews ), Snowflake lacks transparency in estimating ...
What needs improvement with Snowflake?
There is a need for a tool to help me estimate the cost of using Snowflake. Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently r...
 

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: June 2025.
858,327 professionals have used our research since 2012.