Apache Flink vs Software AG Apama comparison

Apache and Software AG are both solutions in the Streaming Analytics category. Apache is ranked #5 with an average rating of 7.6, while Software AG is ranked #21 with an average rating of 7.0. Apache holds a 12.6% mindshare in SA, compared to Software AG’s 0.2% mindshare. Additionally, 94% of Apache users are willing to recommend the solution, compared to 100% of Software AG users who would recommend it.

Apache Flink

Read 16 Apache Flink reviews

5,503 Views
3,955 Comparison Views

94% willing to recommend

Software AG Apama

Read 1 Software AG Apama review

123 Views
71 Comparison Views

100% willing to recommend

Apache Flink

Software AG Apama

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Executive Summary

We performed a comparison between Apache Flink and Software AG Apama based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics.

To learn more, read our detailed Streaming Analytics Report (Updated: February 2025).

Buyer's Guide

Streaming Analytics

February 2025

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Helped 842,592 peers since 2012

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

5th

Average Rating

7.6

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Software AG Apama

Ranking in Streaming Analytics

21st

Average Rating

7.0

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

CEP (1st)

Mindshare comparison

As of March 2025, in the Streaming Analytics category, the mindshare of Apache Flink is 12.6%, up from 9.4% compared to the previous year. The mindshare of Software AG Apama 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

Ilya Afanasyev

Senior Software Development Engineer at Yahoo!

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.

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Shekhar Pathak

Sr Executive Accounts at a computer software company with 1,001-5,000 employees

A tool to send out promotional notifications that need to improve areas, like deployment and maintenance

Software AG Apama should support offline scenarios as it may not always be possible to stay connected with the cloud. The solution should be deployed on an on-premises model, and it should be able to handle offline scenarios. If certain rules are set in Software AG Apama, then it should be able to execute them without being connected to an open internet source. With Software AG Apama, one may face challenges since it is difficult to find people with the right skill set to operate it. The solution also makes use of a proprietary programming language that is hard to trace in the market. It is better to go with the new options available in the market since Software AG Apama has become an old product. The ease of development and maintenance should be enhanced, but it is difficult due to the use of the proprietary programming language in the product.

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Quotes from Members

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

Pros

"Apache Flink allows you to reduce latency and process data in real-time, making it ideal for such scenarios."

"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."

"Apache Flink offers a range of powerful configurations and experiences for development teams. Its strength lies in its development experience and capabilities."

"Apache Flink's best feature is its data streaming tool."

"It is user-friendly and the reporting is good."

"Easy to deploy and manage."

"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."

"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."

More Apache Flink pros

"The most valuable feature of the solution is the ability that it provides its users to handle different kinds of rules."

Cons

"Amazon's CloudFormation templates don't allow for direct deployment in the private subnet."

"PyFlink is not as fully featured as Python itself, so there are some limitations to what you can do with it."

"Apache Flink should improve its data capability and data migration."

"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."

"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."

"In terms of improvement, there should be better reporting. You can integrate with reporting solutions but Flink doesn't offer it themselves."

"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."

More Apache Flink cons

"The ease of development and maintenance should be enhanced, but it is difficult due to the use of the proprietary programming language in the product."

Pricing and Cost Advice

"The solution is open-source, which is free."

"Apache Flink is open source so we pay no licensing for the use of the software."

"This is an open-source platform that can be used free of charge."

"It's an open-source solution."

"It's an open source."

"A commercial license is required to operate Software AG Apama."

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Top Industries

By visitors reading reviews

Financial Services Firm

23%

Computer Software Company

16%

Manufacturing Company

Retailer

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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. ...

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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.

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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.

See all answers

What do you like most about Software AG Apama?

The most valuable feature of the solution is the ability that it provides its users to handle different kinds of rules.

See all answers

What is your experience regarding pricing and costs for Software AG Apama?

A commercial license is required to operate Software AG Apama.

See all answers

What needs improvement with Software AG Apama?

See all answers

Comparisons

Spring Cloud Data Flow vs Apache Flink

Compared 25% of the time

Databricks vs Apache Flink

Compared 21% of the time

Azure Stream Analytics vs Apache Flink

Compared 12% of the time

Amazon Kinesis vs Apache Flink

Compared 11% of the time

Google Cloud Dataflow vs Apache Flink

Compared 8% of the time

More Apache Flink Competitors

No data available

Product Reports

Buyer's Guide

Apache Flink

March 2025

Download Apache Flink product report

Buyer's Guide

Streaming Analytics

February 2025

Download Software AG Apama product report

Also Known As

Flink

Progress Apama

Overview

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.

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

Enables both sell-side and buy-side traders to leverage proprietary trading strategies.

Software AG

Sample Customers

LogRhythm, Inc., Inter-American Development Bank, Scientific Technologies Corporation, LotLinx, Inc., Benevity, Inc.

Okasan Online Securities

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics. Updated: February 2025.

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