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Apache Flink vs Databricks comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

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

Apache Flink
Ranking in Streaming Analytics
6th
Average Rating
7.6
Reviews Sentiment
6.9
Number of Reviews
16
Ranking in other categories
No ranking in other categories
Databricks
Ranking in Streaming Analytics
1st
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
88
Ranking in other categories
Cloud Data Warehouse (7th), Data Science Platforms (1st)
 

Mindshare comparison

As of April 2025, in the Streaming Analytics category, the mindshare of Apache Flink is 13.2%, up from 9.5% compared to the previous year. The mindshare of Databricks is 14.6%, up from 10.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Ilya Afanasyev - PeerSpot reviewer
A great solution with an intricate system and allows for batch data processing
We value this solution's intricate system because it comes with a state inside the mechanism and product. The system allows us to process batch data, stream to real-time and build pipelines. Additionally, we do not need to process data from the beginning when we pause, and we can continue from the same point where we stopped. It helps us save time as 95% of our pipelines will now be on Amazon, and we'll save money by saving time.
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.

Quotes from Members

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

Pros

"The product helps us to create both simple and complex data processing tasks. Over time, it has facilitated integration and navigation across multiple data sources tailored to each client's needs. We use Apache Flink to control our clients' installations."
"Apache Flink offers a range of powerful configurations and experiences for development teams. Its strength lies in its development experience and capabilities."
"Allows us to process batch data, stream to real-time and build pipelines."
"The event processing function is the most useful or the most used function. The filter function and the mapping function are also very useful because we have a lot of data to transform. For example, we store a lot of information about a person, and when we want to retrieve this person's details, we need all the details. In the map function, we can actually map all persons based on their age group. That's why the mapping function is very useful. We can really get a lot of events, and then we keep on doing what we need to do."
"This is truly a real-time solution."
"The setup was not too difficult."
"Easy to deploy and manage."
"Apache Flink is meant for low latency applications. You take one event opposite if you want to maintain a certain state. When another event comes and you want to associate those events together, in-memory state management was a key feature for us."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"It offers AI functionalities that assist with code management and machine learning processes."
"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."
"The setup was straightforward."
"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"The technical support is good."
"Easy to use and requires minimal coding and customizations."
"It is fast, it's scalable, and it does the job it needs to do."
 

Cons

"The solution could be more user-friendly."
"There is room for improvement in the initial setup process."
"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."
"The state maintains checkpoints and they use RocksDB or S3. They are good but sometimes the performance is affected when you use RocksDB for checkpointing."
"In a future release, they could improve on making the error descriptions more clear."
"Apache Flink should improve its data capability and data migration."
"One way to improve Flink would be to enhance integration between different ecosystems. For example, there could be more integration with other big data vendors and platforms similar in scope to how Apache Flink works with Cloudera. Apache Flink is a part of the same ecosystem as Cloudera, and for batch processing it's actually very useful but for real-time processing there could be more development with regards to the big data capabilities amongst the various ecosystems out there."
"Apache Flink's documentation should be available in more languages."
"The tool should improve its integration with other products."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."
"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."
"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."
"Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems."
"I believe that this product could be improved by becoming more user-friendly."
"Implementation of Databricks is still very code heavy."
"In the next release, I would like to see more optimization features."
 

Pricing and Cost Advice

"This is an open-source platform that can be used free of charge."
"Apache Flink is open source so we pay no licensing for the use of the software."
"It's an open-source solution."
"It's an open source."
"The solution is open-source, which is free."
"We only pay for the Azure compute behind the solution."
"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
"We have only incurred the cost of our AWS cloud services. This is because during this period, Databricks provided us with an extended evaluation period, and we have not spent much money yet. We are just starting to incur costs this month, I will know more later on the full cost perspective."
"Databricks' cost could be improved."
"I would rate Databricks' pricing seven out of ten."
"We're charged on what the data throughput is and also what the compute time is."
"The pricing depends on the usage itself."
"I rate the price of Databricks as eight out of ten."
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Computer Software Company
16%
Manufacturing Company
7%
Retailer
4%
Financial Services Firm
17%
Computer Software Company
11%
Manufacturing Company
9%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Apache Flink?
The product helps us to create both simple and complex data processing tasks. Over time, it has facilitated integration and navigation across multiple data sources tailored to each client's needs. ...
What is your experience regarding pricing and costs for Apache Flink?
The solution is expensive. I rate the product’s pricing a nine out of ten, where one is cheap and ten is expensive.
What needs improvement with Apache Flink?
There are more libraries that are missing and also maybe more capabilities for machine learning. It could have a friendly user interface for pipeline configuration, deployment, and monitoring.
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...
 

Also Known As

Flink
Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
 

Overview

 

Sample Customers

LogRhythm, Inc., Inter-American Development Bank, Scientific Technologies Corporation, LotLinx, Inc., Benevity, Inc.
Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Find out what your peers are saying about Apache Flink vs. Databricks and other solutions. Updated: March 2025.
844,944 professionals have used our research since 2012.