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Databricks vs Upsolver comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Databricks
Ranking in Streaming Analytics
1st
Average Rating
8.2
Number of Reviews
82
Ranking in other categories
Data Science Platforms (1st)
Upsolver
Ranking in Streaming Analytics
19th
Average Rating
8.0
Number of Reviews
1
Ranking in other categories
Data Integration (43rd)
 

Mindshare comparison

As of November 2024, in the Streaming Analytics category, the mindshare of Databricks is 14.0%, up from 9.6% compared to the previous year. The mindshare of Upsolver is 0.2%, down from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Dunstan Matekenya - PeerSpot reviewer
Jul 10, 2024
Process large-scale data sets and integrates with Apache Spark with notebook environment
I primarily use Databricks to process large-scale data sets with Apache Spark. My main use case is processing large data sets, such as 600 GB or 800 GB Databricks integrates natively with Apache Spark, which I use as a processing engine for large-scale datasets. This native integration is one of…
Kireet Kokala - PeerSpot reviewer
Aug 13, 2024
Provides ETL tools with stability at a competitive price
When I test-drove Upsolver for a consulting company, I used it in POC to stream and ingest data. The goal was to move data from a source, possibly SQL Server, into a destination like Snowflake or Redshift. The POC aimed to evaluate Upsolver against StreamSets, the competition for ETL tasks. The use…

Quotes from Members

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

Pros

"Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours."
"The processing capacity is tremendous in the database."
"I like cloud scalability and data access for any type of user."
"Its lightweight and fast processing are valuable."
"The solution is an impressive tool for data migration and integration."
"The most valuable feature of Databricks is the integration with Microsoft Azure."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."
 

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."
"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."
"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."
"The product could be improved regarding the delay when switching to higher-performing virtual machines compared to other platforms."
"I have seen better user interfaces, so that is something that can be improved."
"Implementation of Databricks is still very code heavy."
"Can be improved by including drag-and-drop features."
"It should have more compatible and more advanced visualization and machine learning libraries."
"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."
 

Pricing and Cost Advice

"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."
"The solution requires a subscription."
"I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly."
"Price-wise, I would rate Databricks a three out of five."
"I would rate the tool’s pricing an eight out of ten."
"Databricks are not costly when compared with other solutions' prices."
"We pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations."
"The cost is around $600,000 for 50 users."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
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 is your experience regarding pricing and costs for Upsolver?
It was competitively priced and within the customer's budget.
What needs improvement with Upsolver?
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 aggregat...
What is your primary use case for Upsolver?
When I test-drove Upsolver for a consulting company, I used it in POC to stream and ingest data. The goal was to move data from a source, possibly SQL Server, into a destination like Snowflake or R...
 

Comparisons

No data available
 

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
Information Not Available
Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Confluent and others in Streaming Analytics. Updated: October 2024.
814,763 professionals have used our research since 2012.