Apache Flink Reviews

Name: Apache Flink
Brand: Apache
Rating: 3.8 (16 reviews)

Vendor: Apache

3.8 out of 5

16 reviews
94% willing to recommend

161 followers

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What is Apache Flink?

Apache Flink is an open-source batch and stream data processing engine. It can be used for batch, micro-batch, and real-time processing. Flink is a programming model that combines the benefits of batch processing and streaming analytics by providing a unified programming interface for both data sources, allowing users to write programs that seamlessly switch between the two modes. It can also be used for interactive queries.

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Apache Flink is the #5 ranked solution in Streaming Analytics tools. PeerSpot users give Apache Flink an average rating of 7.6 out of 10. Based on the analysis of the 16 most recent Apache Flink reviews, the overall sentiment is positive, with a sentiment score of 6.9. Apache Flink is most commonly compared to Databricks: Apache Flink vs Databricks. Apache Flink is popular among the large enterprise segment, accounting for 71% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 23% of all views.

Helped 825,399 peers since 2012

Featured reviews

Ilya Afanasyev

Senior Software Development Engineer at Yahoo!

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.

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Armando Becerril

Partner / Head of Data & Analytics at Intelligence Software Consulting

The solution is is difficult to manage and handle. Apache Flink is one of the main solutions for real-time decision-making and rapid site provision on Azure. Currently, it's predominantly utilized for data engineering projects rather than AI initiatives, although it can indirectly influence analytics, machine learning, and other products in the stack. The solution is resilient and store more capabilities and features. Overall, I rate the solution an eight out of ten.

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Sunil Morya

Consultant at Tata Consultancy

The issue we had with Flink was that when you had to refer the schema into the input data stream, it had to be done directly into code. The XLS format where the schema is stored, had to be stored in Python. If the schema changes, you have to redeploy Flink because the basic tasks and jobs are already running. That's one disadvantage. Another was a restriction with Amazon's CloudFormation templates which don't allow for direct deployment in the private subnet. You have to deploy into the public subnet and then from the Amazon console, specify a different private subnet that requires a lot of settings. In general, the integration with Amazon products was not good and was very time-consuming. I'd like to think that has changed.

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Apache Flink mindshare

As of January 2025, the mindshare of Apache Flink in the Streaming Analytics category stands at 12.4%, up from 10.5% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Streaming Analytics

PeerAnalyst reports

Type	Title	Date
Category	Streaming Analytics	Jan 2, 2025	Download
Product	Reviews, tips, and advice from real users	Jan 2, 2025	Download
Comparison	Apache Flink vs Databricks	Jan 2, 2025	Download
Comparison	Apache Flink vs Amazon Kinesis	Jan 2, 2025	Download
Comparison	Apache Flink vs Confluent	Jan 2, 2025	Download

Title	Rating	Mindshare	Recommending
Databricks	4.1	14.6%	96%	84 interviews Add to research
Confluent	4.1	8.8%	100%	22 interviews Add to research

Valuable Features

"Apache Flink offers a range of powerful configurations and experiences for development teams. Its strength lies in its development experience and capabilities."
"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."
"It provides us the flexibility to deploy it on any cluster without being constrained by cloud-based limitations."

Room for Improvement

"There are more libraries that are missing and also maybe more capabilities for machine learning."
"Apache Flink should improve its data capability and data migration."
"There is room for improvement in the initial setup process."

Pricing

"It's an open source."
"It's an open-source solution."
"Apache Flink is open source so we pay no licensing for the use of the software."

Service and Support

Users frequently rely on forums and community resources for assistance. Apache Flink's documentation is praised for being comprehensive. Although most don't utilize paid technical support, it's available for serious issues. Open-source nature presents challenges in accountability, often handled by alternative resources. Many users efficiently resolve issues without needing direct support, indicating that the tool is user-friendly. Some prefer using external support, like Amazon's team, to complement community-driven solutions.

These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.

Download our Apache Flink Buyer's Guide for additional reliable information.

Review data by company size

By reviewers

By visitors reading reviews

Top industries

By visitors reading reviews

Financial Services Firm

23%

Computer Software Company

17%

Manufacturing Company

Healthcare Company

Educational Organization

Retailer

Insurance Company

Energy/Utilities Company

Media Company

Recreational Facilities/Services Company

Construction Company

Real Estate/Law Firm

Legal Firm

Government

University

Comms Service Provider

Transportation Company

Hospitality Company

Logistics Company

Wholesaler/Distributor

Consumer Goods Company

Non Profit

Outsourcing Company

Performing Arts

Pharma/Biotech Company

Engineering Company

Mining And Metals Company

Compare Apache Flink with alternative products

Learn more about Apache Flink

Flink can be used as an alternative to MapReduce for executing iterative algorithms on large datasets in parallel. It was developed specifically for large to extremely large data sets that require complex iterative algorithms.

Flink is a fast and reliable framework developed in Java, Scala, and Python. It runs on the cluster that consists of data nodes and managers. It has a rich set of features that can be used out of the box in order to build sophisticated applications.

Flink has a robust API and is ready to be used with Hadoop, Cassandra, Hive, Impala, Kafka, MySQL/MariaDB, Neo4j, as well as any other NoSQL database.

Apache Flink Features

Distributed execution of streaming programs on clusters of computers
Support for multiple data sources and sinks: this includes Hadoop file systems, databases, and other data sources
Streaming SQL query engine with support for windowing functions
Low latency query execution in milliseconds
Runs in a distributed fashion: it can be deployed on multiple machines or nodes to increase performance and reliability of data processing pipelines.
Powerful API that supports both batch and streaming applications
Runs on clusters of commodity hardware with minimal configuration
Can be integrated with other technologies, such as Apache Spark for complex data mining

Apache Flink Benefits

Ease of use: Flink has an intuitive API and provides high-level abstractions for handling data streams. Even beginners in the field can work with the platform with ease.

Fault tolerance: Flink can automatically detect and recover from failures in the system.

Scalability: Flink scales to thousands of nodes. It can run on clusters of any size and the user does not have to worry about managing the cluster.

Reviews from Real Users

Apache Flink stands out among its competitors for a number of reasons. Two major ones are its low latency and its user-friendly interface. PeerSpot users take note of the advantages of these features in their reviews:

The head of data and analytics at a computer software company notes, “The top feature of Apache Flink is its low latency for fast, real-time data. Another great feature is the real-time indicators and alerts which make a big difference when it comes to data processing and analysis.”

Ertugrul A., manager at a computer software company, writes, “It's usable and affordable. It is user-friendly and the reporting is good.”

Apache Flink was previously known as Flink.