Apache Kafka vs. Apigee Edge

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Kafka
Score 8.4 out of 10
N/A
Apache Kafka is an open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java. The Kafka event streaming platform is used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.N/A
Apigee Edge
Score 8.2 out of 10
N/A
Apigee Edge is an API management platform now owned and offered by Google, since Google acquired Apigee in 2016.N/A
Pricing
Apache KafkaApigee Edge
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache KafkaApigee Edge
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache KafkaApigee Edge
Considered Both Products
Apache Kafka

No answer on this topic

Apigee Edge
Chose Apigee Edge
Apigee is the best in the market in terms of API Analytics Apigee is having wonderful Documentation with short videos Security is a major concern and Apigee provides an easily configurable policy to secure API Quota and rate-limit is again very easy to configure on every API …
Top Pros
Top Cons
Features
Apache KafkaApigee Edge
API Management
Comparison of API Management features of Product A and Product B
Apache Kafka
-
Ratings
Apigee Edge
9.4
7 Ratings
14% above category average
API access control00 Ratings9.07 Ratings
Rate limits and usage policies00 Ratings9.07 Ratings
API usage data00 Ratings9.07 Ratings
API user onboarding00 Ratings9.97 Ratings
API versioning00 Ratings9.97 Ratings
Usage billing and payments00 Ratings9.06 Ratings
API monitoring and logging00 Ratings9.97 Ratings
Best Alternatives
Apache KafkaApigee Edge
Small Businesses

No answers on this topic

NGINX
NGINX
Score 9.1 out of 10
Medium-sized Companies
IBM MQ
IBM MQ
Score 9.0 out of 10
NGINX
NGINX
Score 9.1 out of 10
Enterprises
IBM MQ
IBM MQ
Score 9.0 out of 10
NGINX
NGINX
Score 9.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache KafkaApigee Edge
Likelihood to Recommend
8.3
(18 ratings)
9.0
(7 ratings)
Likelihood to Renew
9.0
(2 ratings)
9.0
(1 ratings)
Usability
10.0
(1 ratings)
9.0
(1 ratings)
Support Rating
8.4
(4 ratings)
6.0
(1 ratings)
User Testimonials
Apache KafkaApigee Edge
Likelihood to Recommend
Apache
Apache Kafka is well-suited for most data-streaming use cases. Amazon Kinesis and Azure EventHubs, unless you have a specific use case where using those cloud PaAS for your data lakes, once set up well, Apache Kafka will take care of everything else in the background. Azure EventHubs, is good for cross-cloud use cases, and Amazon Kinesis - I have no real-world experience. But I believe it is the same.
Read full review
Google
Few scenarios 1. For viewing API analytics, I think it is best in the market 2. For earning money via API monetization 3. Securing API 4. Onboarding legacy APIs to provide modern REST endpoints
Read full review
Pros
Apache
  • Really easy to configure. I've used other message brokers such as RabbitMQ and compared to them, Kafka's configurations are very easy to understand and tweak.
  • Very scalable: easily configured to run on multiple nodes allowing for ease of parallelism (assuming your queues/topics don't have to be consumed in the exact same order the messages were delivered)
  • Not exactly a feature, but I trust Kafka will be around for at least another decade because active development has continued to be strong and there's a lot of financial backing from Confluent and LinkedIn, and probably many other companies who are using it (which, anecdotally, is many).
Read full review
Google
  • Better exception handling with the Raise exception policies help to monitor the flow by setting up the flow conditions.
  • Easy development of a Proxy and APIs with much less tutoring and helps make getting started for new users easy.
  • Very good documentation and blog with details of most common failures and error handling.
  • A very very easy to use console.
Read full review
Cons
Apache
  • Sometimes it becomes difficult to monitor our Kafka deployments. We've been able to overcome it largely using AWS MSK, a managed service for Apache Kafka, but a separate monitoring dashboard would have been great.
  • Simplify the process for local deployment of Kafka and provide a user interface to get visibility into the different topics and the messages being processed.
  • Learning curve around creation of broker and topics could be simplified
Read full review
Google
  • Only one user can be active in a proxy at a time
  • No version control
  • Prohibited from using JSON.stringify on Apigee objects (tokens)
  • Debugging is difficult
  • Unable to rename or delete policies without bumping revision
  • Why would anyone give a js policy one name, display name something else, and script a different name?
  • 'Trace' limited to only 20 transactions
  • UI allows users to add target servers, but users must utilize the api to turn on SSL.
  • I'm sure there's more, they just aren't coming to mind right now.
  • Apigee forgets (expires?) your password at random intervals without notice. Every few weeks, or days, sometimes even three times in one day, I'll attempt to login to Apigee and my password will be 'wrong'. I've reset my password and Apigee still claims it's wrong. I've had to reset my password three times before it finally let me log back in.
Read full review
Likelihood to Renew
Apache
Kafka is quickly becoming core product of the organization, indeed it is replacing older messaging systems. No better alternatives found yet
Read full review
Google
I am not the one deciding whether to use apigee or not really. But personally, I would recommend the use of it as developing APIs on it is easy. And as a mediator between backend servers, we could easily modify request and responses in it without touching any backend code while having a centralize gateway to access our backend APIs too.
Read full review
Usability
Apache
Apache Kafka is highly recommended to develop loosely coupled, real-time processing applications. Also, Apache Kafka provides property based configuration. Producer, Consumer and broker contain their own separate property file
Read full review
Google
Support has helped us to resolved all the queries and community support was also good.
Read full review
Support Rating
Apache
Support for Apache Kafka (if willing to pay) is available from Confluent that includes the same time that created Kafka at Linkedin so they know this software in and out. Moreover, Apache Kafka is well known and best practices documents and deployment scenarios are easily available for download. For example, from eBay, Linkedin, Uber, and NYTimes.
Read full review
Google
Quite hard to get support, at least on the coding side, when we encounter blockers. But general concerns, they would schedule a call to you for them to get a whole picture of your concern. Albeit in my experience, bad really as they haven't replied about the progress, but otherwise seems to have been fixed.
Read full review
Alternatives Considered
Apache
I used other messaging/queue solutions that are a lot more basic than Confluent Kafka, as well as another solution that is no longer in the market called Xively, which was bought and "buried" by Google. In comparison, these solutions offer way fewer functionalities and respond to other needs.
Read full review
Google
Apigee is the best in the market in terms of API Analytics Apigee is having wonderful Documentation with short videos Security is a major concern and Apigee provides an easily configurable policy to secure API Quota and rate-limit is again very easy to configure on every API basis It provides various policies to transform the response from one form to another form e.g. JSON to XML or XML to JSON
Read full review
Return on Investment
Apache
  • Positive: Get a quick and reliable pub/sub model implemented - data across components flows easily.
  • Positive: it's scalable so we can develop small and scale for real-world scenarios
  • Negative: it's easy to get into a confusing situation if you are not experienced yet or something strange has happened (rare, but it does). Troubleshooting such situations can take time and effort.
Read full review
Google
  • As a public entity it is hard to say how much ROI we can have. We have yet to create a billing and ROI plan. We are thinking of other ways to create ROI, possibly through data/service barter.
Read full review
ScreenShots