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Databricks vs Mode Enterprise comparison

 

Comparison Buyer's Guide

Executive Summary

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

Databricks
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
92
Ranking in other categories
Cloud Data Warehouse (9th), Data Science Platforms (1st), Data Management Platforms (DMP) (5th), Streaming Analytics (1st)
Mode Enterprise
Average Rating
7.4
Reviews Sentiment
4.8
Number of Reviews
6
Ranking in other categories
BI (Business Intelligence) Tools (29th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 9.2%, up 6.7% compared to last year.
Mode Enterprise, on the other hand, focuses on BI (Business Intelligence) Tools, holds 0.9% mindshare, up 0.4% since last year.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
Databricks9.2%
Snowflake16.1%
Teradata8.5%
Other66.2%
Cloud Data Warehouse
BI (Business Intelligence) Tools Market Share Distribution
ProductMarket Share (%)
Mode Enterprise0.9%
Microsoft Power BI9.4%
Tableau Enterprise6.7%
Other83.0%
BI (Business Intelligence) Tools
 

Featured Reviews

SimonRobinson - PeerSpot reviewer
Governance And Engagement Lead
Improved data governance has enabled sensitive data tracking but cost management still needs work
I believe we could improve Databricks integration with cloud service providers. The impact of our current integration has not been particularly good, and it's becoming very expensive for us. The inefficiencies in our implementation, such as not shutting down warehouses when they're not in use or reserving the right number of credits, have led to increased costs. We made several beginner mistakes, such as not taking advantage of incremental loading and running overly complicated queries all the time. We should be using ETL tools to help us instead of doing it directly in Databricks. We need more experienced professionals to manage Databricks effectively, as it's not as forgiving as other platforms such as Snowflake. I think introducing customer repositories would facilitate easier implementation with Databricks.
Shivkumar Targude - PeerSpot reviewer
Senior Software Engineer at a tech services company with 1,001-5,000 employees
Custom cohort dashboards have transformed customer tracking but still need richer built‑in visuals
From my perspective, adding more custom visualizations as inbuilt features would be greatly beneficial for developers and other teams. For specific visualizations, we currently need to use Python and JavaScript combinations to create great visualizations such as cohort analysis. If these visualizations were added by default to Mode Enterprise, it would be beneficial for all of us. There are common visualizations that are not currently in Mode Enterprise but should be added. There are advantages and disadvantages to the current state. The advantages mainly include the ability to combine all datasets, which definitely reduces time. Because Python and JavaScript are supported, we can develop cohort dashboards, which many other BI tools do not support. Mode Enterprise supports cohort dashboards, which is a significant advantage.

Quotes from Members

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

Pros

"Easy to use and requires minimal coding and customizations."
"The setup was straightforward."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"I would rate them ten out of ten."
"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."
"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."
"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."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"The solution is simple for people from a viewing perspective, not a coding perspective."
"The most valuable feature I would say is the flexibility in editing."
"The most important feature of the solution is the ability to run Python-based scripts."
"Mode Enterprise positively impacted my organization with its clean visualization and slightly faster response times."
"The tool helps to catch results and review them."
"I have used many other BI tools, but when I compare other BI tools with Mode Enterprise, I find it more interesting because it supports Amazon Redshift and cloud-related technology as well as some static-related technology, and it also supports customization through coding with JavaScript and Python."
 

Cons

"In my opinion, areas of Databricks that have room for improvement involve the dashboards. Until recently, everyone used third-party systems such as Power BI to connect to Databricks for dashboards and reports, but they're now coming up with their IBI dashboard, and I think they're on the right track to improve that even further."
"Databricks can improve by making the documentation better."
"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"There is room for improvement in visualization."
"I think setting up the whole account for one person and giving access are areas that can be difficult to manage and should be made a little easier."
"One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files. Standardization of file paths on the system could help, as engineers sometimes struggle."
"The API deployment and model deployment are not easy on the Databricks side."
"I think in terms of User Interface, I would say it can be better."
"The solution could run faster."
"Mode Enterprise can be improved by reducing the cost, as I think the enterprise version is much costlier."
"The data visualization is cumbersome in Mode Analytics. I want the solution to add a map that has an easy interface. The UI is slow sometimes."
"Mode Analytics needs to improve the overall user experience."
"From my perspective, adding more custom visualizations as inbuilt features would be greatly beneficial for developers and other teams."
 

Pricing and Cost Advice

"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."
"Databricks are not costly when compared with other solutions' prices."
"The licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts."
"The solution is based on a licensing model."
"It is an expensive tool. The licensing model is a pay-as-you-go one."
"The cost is around $600,000 for 50 users."
"The pricing depends on the usage itself."
"Databricks' cost could be improved."
"The pricing is per user."
"Mode Analytics is cheap compared to other tools."
"My decision-maker found the pricing expensive, but it is okay for me."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
9%
Computer Software Company
9%
Healthcare Company
6%
Media Company
13%
Manufacturing Company
11%
Computer Software Company
10%
Insurance Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business25
Midsize Enterprise12
Large Enterprise56
No data available
 

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 needs improvement with Mode Analytics?
From my perspective, adding more custom visualizations as inbuilt features would be greatly beneficial for developers and other teams. For specific visualizations, we currently need to use Python a...
What is your primary use case for Mode Analytics?
Mode Enterprise is being used for dashboard purposes only, specifically for custom dashboards. For the e-commerce domain, we use Mode Enterprise to track customers, such as finding out a customer's...
What advice do you have for others considering Mode Analytics?
Regarding licensing, I cannot provide detailed information on that topic. However, I can say that Power BI is open-source. If Mode Enterprise were provided as open-source, more people could start u...
 

Comparisons

 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
No data available
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Lyft, Zenefits, Twitch, Trello, Clover, Grovo, CrowdFlower, Segment, Everlane, Pocket, Highfive
Find out what your peers are saying about Snowflake Computing, Microsoft, Teradata and others in Cloud Data Warehouse. Updated: January 2026.
881,114 professionals have used our research since 2012.