Databricks vs Upsolver comparison

Databricks and Upsolver are both solutions in the Streaming Analytics category. Databricks is ranked #1 with an average rating of 8.4, while Upsolver is ranked #20 with an average rating of 8.5. Databricks holds a 13.1% mindshare in SA, compared to Upsolver’s 0.4% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of Upsolver users who would recommend it.

Databricks

Read 91 Databricks reviews

22,527 Views
4,055 Comparison Views

96% willing to recommend

Upsolver

Read 2 Upsolver reviews

368 Views
103 Comparison Views

100% willing to recommend

Databricks

Upsolver

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between Databricks and Upsolver based on real PeerSpot user reviews.

Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Databricks vs. Upsolver Report (Updated: July 2025).

Buyer's Guide

Databricks vs. Upsolver

July 2025

Download the complete report

Helped 867,497 peers since 2012

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

Ranking in Streaming Analytics

1st

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (9th), Data Science Platforms (1st)

Upsolver

Ranking in Streaming Analytics

20th

Average Rating

8.6

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Integration (37th)

Mindshare comparison

As of September 2025, in the Streaming Analytics category, the mindshare of Databricks is 13.1%, up from 12.5% compared to the previous year. The mindshare of Upsolver is 0.4%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Market Share Distribution
Product	Market Share (%)
Databricks	13.1%
Upsolver	0.4%
Other	86.5%

Streaming Analytics

Featured Reviews

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

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.

Read full review

Snehasish Das

Technology Leader at eTCaaS

Allows for data to be moved across platforms and different data technologies

The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies. Upsolver does this in a quick time, unlike traditional processes which are time-consuming. Additionally, it offers scalability for large volumes of data, with performance and ease of cloud-native integration.

Read full review

Quotes from Members

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

Pros

"The setup was straightforward."

"The setup is quite easy."

"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."

"It is fast, it's scalable, and it does the job it needs to do."

"Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."

"Databricks has helped us have a good presence in data."

"The built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly."

"It helps integrate data science and machine learning capabilities."

More Databricks pros

"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."

"The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies."

"Customer service is excellent, and I would rate it between eight point five to nine out of ten."

Cons

"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."

"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."

"There would also be benefits if more options were available for workers, or the clusters of the two points."

"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."

"Costs can quickly add up if you don't plan for it."

"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."

"Doesn't provide a lot of credits or trial options."

"The solution has some scalability and integration limitations when consolidating legacy systems."

More Databricks cons

"On the stability side, I would rate it seven out of ten. Using multiple cloud providers and data engineering technologies creates complexity, and managing different plugins is not always easy, but they are working on it."

"Upsolver excels in ETL and data aggregation, while ThoughtSpot is strong in natural language processing for querying datasets. Combining these tools can be very effective: Upsolver handles aggregation and ETL, and ThoughtSpot allows for natural language queries. There’s potential for highlighting these integrations in the future."

"There is room for improvement in query tuning."

Pricing and Cost Advice

"I would rate the tool’s pricing an eight out of ten."

"The licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts."

"The cost for Databricks depends on the use case. I work on it as a consultant, so I'm using the client's Databricks, so it depends on how big the client is."

"Price-wise, I would rate Databricks a three out of five."

"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."

"I would rate Databricks' pricing seven out of ten."

"The pricing depends on the usage itself."

"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."

More Databricks pricing and cost advice

"Upsolver is affordable at approximately $225 per terabyte per year."

See which vendors are best for you

Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.

See recommendations

867,497 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	25
Midsize Enterprise	12
Large Enterprise	56

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 ...

See all answers

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...

See all answers

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...

See all answers

What is your experience regarding pricing and costs for Upsolver?

Upsolver is affordable at approximately $225 per terabyte per year. Compared to what I know from others, it's cheaper than many other products.

See all answers

What needs improvement with Upsolver?

There is room for improvement in query tuning. Upsolver could do a more in-depth analysis in employing machine power, such as CPU and memory, to enhance query performance. Furthermore, allocating C...

See all answers

What is your primary use case for Upsolver?

I am working as a consultant and currently have my own consultancy services. I provide services to companies that are data-heavy and looking for data engineering solutions for their business needs....

See all answers

Comparisons

Dataiku vs Databricks

Compared 9% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 6% of the time

Tableau Enterprise vs Databricks

Compared 5% of the time

More Databricks Competitors

Rivery vs Upsolver

Compared 46% of the time

More Upsolver Competitors

Product Reports

Buyer's Guide

Databricks

September 2025

Download Databricks product report

Buyer's Guide

Data Integration

August 2025

Download Upsolver product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

No data available

Overview

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

Databricks

Upsolver's mission is to turn engineering-intensive data lakes into easy-to-use repositories that serve 50X more data professionals compared to the status-quo today. Upsolver cuts 95% from the tedious process of preparing event data for analytics and machine learning, using a visual SQL-based interface, a cloud-native data platform and deep technology for stream-processing, indexing and eventually-consistent file systems.

Upsolver

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware

Information Not Available

Buyer's Guide

Databricks vs. Upsolver

July 2025

Free Report: Databricks vs. Upsolver

Find out what your peers are saying about Databricks vs. Upsolver and other solutions. Updated: July 2025.

DOWNLOAD NOW

867,497 professionals have used our research since 2012.

See our Databricks vs. Upsolver report.

See our list of best Streaming Analytics vendors.

We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.