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Databricks vs Spring Cloud Data Flow 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:
 

Customer Service

Sentiment score
6.8
Databricks support is praised for technical expertise and engagement, but experiences vary due to response times and Microsoft partner handling.
No sentiment score available
 

Room For Improvement

Sentiment score
5.8
Databricks faces challenges with visualization, integration, costs, error clarity, libraries, interfaces, documentation, onboarding, automation, governance, and performance.
No sentiment score available
 

Scalability Issues

Sentiment score
8.2
Databricks offers significant, praised scalability from megabytes to petabytes, supporting vertical and horizontal scaling with auto-scaling features.
No sentiment score available
 

Setup Cost

Sentiment score
7.0
Databricks pricing varies greatly based on usage and cluster type, often considered expensive with additional cloud storage costs.
No sentiment score available
 

Stability Issues

Sentiment score
7.7
Databricks is highly stable and reliable, with minimal issues reported, especially during heavy processes, and receives high user ratings.
No sentiment score available
 

Valuable Features

Sentiment score
8.5
Databricks offers user-friendly large-scale analytics, seamless integration, versatile coding, collaborative tools, and efficient big data handling with extensive cloud support.
No sentiment score available
 

Categories and Ranking

Databricks
Ranking in Streaming Analytics
1st
Average Rating
8.2
Reviews Sentiment
7.4
Number of Reviews
84
Ranking in other categories
Data Science Platforms (1st)
Spring Cloud Data Flow
Ranking in Streaming Analytics
10th
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
9
Ranking in other categories
Data Integration (22nd)
 

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 Spring Cloud Data Flow is 5.0%, up from 4.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Dunstan Matekenya - PeerSpot reviewer
Process large-scale data sets and integrates with Apache Spark with notebook environment
Databricks integrates natively with Apache Spark, which I use as a processing engine for large-scale datasets. This native integration is one of its strengths. Another strength is that the platform makes it very easy to manage resources. For example, setting up a cluster of five or fifteen nodes is straightforward with Databricks. The notebook environment is also excellent, making it easy to perform various tasks.
NitinGoyal - PeerSpot reviewer
Has a plug-and-play model and provides good robustness and scalability
The solution's community support could be improved. I don't know why the Spring Cloud Data Flow community is not very strong. Community support is very limited whenever you face any problem or are stuck somewhere. I'm not sure whether it has improved in the last six months because this pipeline was set up almost two years ago. I struggled with that a lot. For example, there was limited support whenever I got an exception and sought help from Stack Overflow or different forums. Interacting with Kubernetes needs a few certificates. You need to define all the certificates within your application. With the help of those certificates, your Java application or Spring Cloud Data Flow can interact with Kubernetes. I faced a lot of hurdles while placing those certificates. Despite following the official documentation to define all the replicas, readiness, and liveliness probes within the Spring Cloud Data Flow application, it was not working. So, I had to troubleshoot while digging in and debugging the internals of Spring Cloud Data Flow at that time. It was just a configuration mismatch, and I was doing nothing weird. There was a small spelling difference between how Spring Cloud Data Flow was expecting it and how I passed it. I was just following the official documentation.
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
6%
Financial Services Firm
28%
Computer Software Company
17%
Manufacturing Company
7%
Retailer
6%
 

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 needs improvement with Spring Cloud Data Flow?
I would improve the dashboard features as they are not very user-friendly. Another area for improvement is the documentation, as it is not very precise. There are limited resources available on Spr...
What is your primary use case for Spring Cloud Data Flow?
I am a developer using Spring Cloud Dataflow. We primarily use it to convert our applications from monolithic to microservices. The solution is used for scheduling tasks in a specific order and ens...
What advice do you have for others considering Spring Cloud Data Flow?
My advice would be to thoroughly review the documentation and understand if Spring Cloud Dataflow is the right solution for your application. For applications with only one or two microservices, it...
 

Also Known As

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

Learn More

 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Information Not Available
Find out what your peers are saying about Databricks vs. Spring Cloud Data Flow and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.