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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

"Another feature is how Flink handles its radiuses. It has something called the checkpointing concept. You're dealing with billions and billions of requests, so your system is going to fail in large storage systems. Flink handles this by using the concept of checkpointing and savepointing, where they write the aggregated state into some separate storage. So in case of failure, you can basically recall from that state and come back."
"With Flink, it provides out-of-the-box checkpointing and state management. It helps us in that way. When Storm used to restart, sometimes we would lose messages. With Flink, it provides guaranteed message processing, which helped us. It also helped us with maintenance or restarts."
"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."
"This is truly a real-time solution."
"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."
"Allows us to process batch data, stream to real-time and build pipelines."
"It is user-friendly and the reporting is good."
"It provides us the flexibility to deploy it on any cluster without being constrained by cloud-based limitations."
"The solution offers a free community version."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"It helps integrate data science and machine learning capabilities."
"The initial setup is pretty easy."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"The ability to stream data and the windowing feature are valuable."
"The setup was straightforward."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
 

Cons

"In terms of stability with Flink, it is something that you have to deal with every time. Stability is the number one problem that we have seen with Flink, and it really depends on the kind of problem that you're trying to solve."
"Apache Flink should improve its data capability and data migration."
"The machine learning library is not very flexible."
"There is room for improvement in the initial setup process."
"PyFlink is not as fully featured as Python itself, so there are some limitations to what you can do with it."
"There are more libraries that are missing and also maybe more capabilities for machine learning."
"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."
"The solution could be more user-friendly."
"We'd like a more visual dashboard for analysis It needs better UI."
"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."
"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."
"The product cannot be integrated with a popular coding IDE."
"There has been a significant evolution in databases. One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files."
"I would love an integration in my desktop IDE. For now, I have to code on their webpage."
"The integration and query capabilities can be improved."
"There are no direct connectors — they are very limited."
 

Pricing and Cost Advice

"It's an open-source solution."
"This is an open-source platform that can be used free of charge."
"The solution is open-source, which is free."
"Apache Flink is open source so we pay no licensing for the use of the software."
"It's an open source."
"It is an expensive tool. The licensing model is a pay-as-you-go one."
"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
"We implement this solution on behalf of our customers who have their own Azure subscription and they pay for Databricks themselves. The pricing is more expensive if you have large volumes of data."
"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."
"The solution is affordable."
"The price is okay. It's competitive."
"The billing of Databricks can be difficult and should improve."
"The product pricing is moderate."
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Computer Software Company
15%
Manufacturing Company
7%
Healthcare Company
5%
Financial Services Firm
17%
Computer Software Company
10%
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: April 2025.
848,716 professionals have used our research since 2012.