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.
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New Relic
Score 8.0 out of 10
N/A
New Relic is a SaaS-based web and mobile application performance management provider for the cloud and the datacenter. They provide code-level diagnostics for dedicated infrastructures, the cloud, or hybrid environments and real time monitoring.
$0
No credit card required; 100 GB free ingest per month, 1 free full user + unlimited basic users, 8 days retention, 100 Synthetics Checks
Pricing
Apache Kafka
New Relic
Editions & Modules
No answers on this topic
Free (Forever)
$0
No credit card required; 100 GB free ingest per month, 1 free full user + unlimited basic users, 8 days retention, 100 Synthetics Checks
Telemetry Data Platform
$0.25
per month per extra GB data ingest (after first free 100GB per month)
Incident Intelligence
$0.50
per month per event (after first 1000 free events per month)
Standard
$99
per month per full user (after first free full user - unlimited free basic users)
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.
I have used New Relic in different scenarios like monitoring my production infrastructure and applications which helps us to reduce the downtime of my applications and websites and also I have used the synthetic monitoring feature which helps to proactively monitor our websites availability. Along with this I have also used New Relic for cloud resources cost monitoring which helps to reduce my cloud cost. Also I have used mobile application monitoring which helps me to trace the sessions easily and I can easily reduce my RCA through the help of that.
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).
New Relic APM allows us to follow up transactions across services and trace performance bottlenecks in real-time, crucial when monitoring the processing of energy loads or predictive maintenance algorithms.
It gives us deep visibility into our cloud servers, containers and IOT gateways, so we can catch CPU spikes or memory leaks which can impact the data we ingest from the field devices.
We develop custom dashboards for monitoring trends of power consumption, abnormality in sensors and API health. In conjunction with alerting, it makes sure we are fixing issues before customers even see them.
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
The only issue that we have had with New Relic is that the price might be a little expensive for smaller companies. The amount of data you store in New Relic impacts the cost, and can get away from you if you don't work closely with the vendor. Overall though the application is top notch.
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
I have given this much rating as I am used New Relic in different sectors and for different use cases like its K8s monitoring, infra monitoring, full stack monitoring as compare to other tools New Relic gives data in a formatted and connected way, and also it is giving us value for money. It also launches new features day by day which helps users to track the issue very quickly. It also supports OTel integrations which is the latest trend of observability tools. thats why I had given this much rating to New Relic.
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.
The support team has been really helpful and resolved most of the issues on time. However, for a couple of issues, several follow-ups were needed to elicit a reasonable response. The issue was deeply technical and could have been investigated only by their Architects, and bringing them into the ticket took longer than needed
It's better to start by implementing New Relic in one project and test everything. Try to follow best recommended practices and read all the official documentation. Everything seems well tested. Then, start by installing agents to the rest of your projects and keep a close look to all logs and metrics New Relic gives you.
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.
New Relic has full stack visibility and gives us all options for observability like one stop shop. It gives you front end, backend as well synthetic monitoring capabilities. Every other feature built into one cost model (usually) which ties to data that you send, it helps you leverage all features without having to pay additional charge for feature
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.
