Apache Kafka vs. Astro by Astronomer

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Kafka
Score 8.7 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
Astro by Astronomer
Score 9.0 out of 10
N/A
For data teams looking to increase the availability of trusted data, Astronomer provides Astro, a data orchestration platform, powered by Airflow. Astro enables data engineers, data scientists, and data analysts to build, run, and observe pipelines-as-code. Astronomer is the driving force behind Apache Airflow™, the de facto standard for expressing data flows as code. Airflow is downloaded more than 8 million times each month and is used by hundreds of thousands of teams around the world.N/A
Pricing
Apache KafkaAstro by Astronomer
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache KafkaAstro by Astronomer
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Apache KafkaAstro by Astronomer
Best Alternatives
Apache KafkaAstro by Astronomer
Small Businesses

No answers on this topic

Skyvia
Skyvia
Score 10.0 out of 10
Medium-sized Companies
IBM MQ
IBM MQ
Score 9.0 out of 10
Astera Data Pipeline Builder (Centerprise)
Astera Data Pipeline Builder (Centerprise)
Score 8.8 out of 10
Enterprises
IBM MQ
IBM MQ
Score 9.0 out of 10
Control-M
Control-M
Score 9.4 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache KafkaAstro by Astronomer
Likelihood to Recommend
8.0
(19 ratings)
10.0
(1 ratings)
Likelihood to Renew
9.0
(2 ratings)
-
(0 ratings)
Usability
8.0
(2 ratings)
-
(0 ratings)
Support Rating
8.4
(4 ratings)
-
(0 ratings)
User Testimonials
Apache KafkaAstro by Astronomer
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.
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Astronomer, Inc.
Astronomer is well suited for workflow and dependency management for enterprise-level data lakes. It is not a product for data processing though. Different source systems can be integrated, it also provides powerful interfaces for alerting and monitoring. Easy to build DAGs, graphical UI, API support makes the product more user-friendly as well. Astronomer also does a great job on user training.
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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).
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Astronomer, Inc.
  • Workflow management
  • Wide availability of plugins
  • Dependency management on upstream
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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
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Astronomer, Inc.
  • More language agnostic
  • Flexible fork and join capabilities
  • Near real time UI updates in case of deployment of enhanced DAGs
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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
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Astronomer, Inc.
No answers on this topic
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
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Astronomer, Inc.
No answers on this topic
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.
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Astronomer, Inc.
No answers on this topic
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.
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Astronomer, Inc.
Astronomer is a fast, secure, scalable workload management solution. It provides world-class user training along with easy to interact support.
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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.
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Astronomer, Inc.
  • It helps to build scalable, available and low maintenance workloads
  • Integrated Alerts and notifications helps to detect load issues in the early stages
  • Ensures meeting data SLAs
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