Try our new research platform with insights from 80,000+ expert users

Databricks vs Sisense 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:
 

ROI

Sentiment score
6.5
Databricks offers cloud scalability and ease of use, but financial benefits and effectiveness depend on specific use cases.
Sentiment score
6.6
Sisense offers time-saving benefits with cost-effectiveness, but experiences vary based on existing analytics systems and initial investments.
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 offers highly rated, responsive support with clear documentation, proactive engagement, and multiple contact options, despite occasional delays.
Sentiment score
8.6
Sisense excels in customer service with expert support, responsive assistance, and a strong commitment to client success.
As of now, we are raising issues and they are providing solutions without any problems.
Whenever we reach out, they respond promptly.
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.
The support was very good.
 

Scalability Issues

Sentiment score
7.5
Databricks offers seamless scalability across clouds, efficiently handling data sizes and increasing users, with praised ease and robust performance.
Sentiment score
7.3
Sisense is praised for scalability, though some users report performance issues with large data volumes; security concerns exist.
Databricks is an easily scalable platform.
I would rate the scalability of this solution as very high, about nine out of ten.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
 

Stability Issues

Sentiment score
7.7
Databricks is highly stable and reliable, despite minor issues, effectively managing large data volumes and supporting enterprise use.
Sentiment score
7.8
Sisense is stable and reliable, with minor slowdowns during data import, but users report no major stability issues.
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.
I would rate the stability of Databricks as highly stable, around nine out of ten.
 

Room For Improvement

Databricks needs an improved UI, better integration, affordable pricing, enhanced machine learning, and streamlined, collaborative features.
Sisense users want enhanced large dataset handling, improved dashboards, better data connectivity, and reduced costs with more customization options.
We could use their job clusters, however, that increases costs, which is challenging for us as a startup.
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.
This feature, if made publicly available, may act as a game-changer, considering many global organizations use SAP data for their ERP requirements.
I would like to see an improvement in the live data connection, specifically making the process faster.
 

Setup Cost

Databricks pricing is usage-based and competitive, with mixed reviews regarding cost-effectiveness, especially for heavy data processing.
Sisense offers a subscription model with competitive pricing, ideal for mid-sized to large enterprises due to its robust features.
It is not a cheap solution.
They were practically dead even from a pricing perspective.
 

Valuable Features

Databricks offers a user-friendly interface, fast querying, multi-language support, and integrated AI for streamlined, collaborative data processing.
Sisense offers user-friendly deployment, rapid data integration, intuitive dashboards, and advanced analytics for enhanced data insights and visualization.
Databricks' capability to process data in parallel enhances data processing speed.
The Unity Catalog is for data governance, and the Delta Lake is to build the lakehouse.
The platform allows us to leverage cloud advantages effectively, enhancing our AI and ML projects.
It offers two ways to access data: by cubing the data or hitting it live.
 

Categories and Ranking

Databricks
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
90
Ranking in other categories
Cloud Data Warehouse (7th), Data Science Platforms (1st), Streaming Analytics (1st)
Sisense
Average Rating
8.8
Reviews Sentiment
7.6
Number of Reviews
41
Ranking in other categories
BI (Business Intelligence) Tools (19th), Cloud Analytics (5th), Reporting (14th), Data Visualization (15th), Embedded BI (9th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Databricks is designed for Cloud Data Warehouse and holds a mindshare of 8.8%, up 3.7% compared to last year.
Sisense, on the other hand, focuses on BI (Business Intelligence) Tools, holds 1.3% mindshare, down 1.5% since last year.
Cloud Data Warehouse
BI (Business Intelligence) Tools
 

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.
Wiboon Thabsuwan - PeerSpot reviewer
Helps businesses save time and offers good integration features
I would say that using Sisense on Linux's platform might not be advantageous for everyone. I am more familiar with Windows than Linux. With Windows, the system performs very fast. Even if your data size consists of like 10,00,00,000 loads or whatever, it works very fast. When using Sisense, it is better to have some people with a very good understanding of Linux. I need more technical people who understand about Linux OS. Only two people would be enough to operate the tool.
report
Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.
851,604 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
10%
Manufacturing Company
9%
Healthcare Company
6%
Financial Services Firm
21%
Computer Software Company
15%
University
6%
Educational Organization
5%
 

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 Sisense?
The solution's technical support team is good.
What needs improvement with Sisense?
I would like to see an improvement in the live data connection, specifically making the process faster. Additionally, incorporating more self-service capabilities would benefit the product.
What is your primary use case for Sisense?
I was looking into some of our business operations with tow truck companies. I focused on evaluating turnaround times for tow trucks to arrive on-site for accidents and how long it took them to cle...
 

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
Ebay, WIX, Wave Accounting, ESPN.com, Magellan Luxury Hotel, Paylogic, Sony, Merck, EDA, One Hour Translation, NASA, Plastic Jungle, Philips, Yahoo
Find out what your peers are saying about Snowflake Computing, Microsoft, Google and others in Cloud Data Warehouse. Updated: May 2025.
851,604 professionals have used our research since 2012.