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Apache NiFi vs Azure Stream Analytics comparison

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Featured Review
Find out what your peers are saying about Amazon, Apache, Zadara and others in Compute Service. Updated: January 2022.
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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
"Visually, this is a good product.""The most valuable features of this solution are ease of use and implementation.""It's an automated flow, where you can build a flow from source to destination, then do the transformation in between."

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"Real-time analytics is the most valuable feature of this solution. I can send the collected data to Power BI in real time.""Technical support is pretty helpful.""Provides deep integration with other Azure resources.""I like the way the UI looks, and the real-time analytics service is aligned to this. That can be helpful if I have to use this on a production service.""The solution has a lot of functionality that can be pushed out to companies.""I like the IoT part. We have mostly used Azure Stream Analytics services for it""The most valuable features are the IoT hub and the Blob storage."

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Cons
"There should be a better way to integrate a development environment with local tools.""I think the UI interface needs to be more user-friendly.""There are some claims that NiFi is cloud-native but we have tested it, and it's not."

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"It is not complex, but it requires some development skills. When the data is sent from Azure Stream Analytics to Power BI, I don't have the access to modify the data. I can't customize or edit the data or do some queries. All queries need to be done in the Azure Stream Analytics.""If something goes wrong, it's very hard to investigate what caused it and why.""Sometimes when we connect Power BI, there is a delay or it throws up some errors, so we're not sure.""There may be some issues when connecting with Microsoft Power BI because we are providing the input and output commands, and there's a chance of it being delayed while connecting.""The collection and analysis of historical data could be better.""Early in the process, we had some issues with stability.""The solution offers a free trial, however, it is too short."

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Pricing and Cost Advice
  • "It's an open-source solution."
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  • "The cost of this solution is less than competitors such as Amazon or Google Cloud."
  • More Azure Stream Analytics Pricing and Cost Advice →

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    Questions from the Community
    Top Answer: 
    I am not involved in this area. I don't have any visibility in the costing and licensing. We have a department that goes through the licensing and once we approve the functions and the performance of… more »
    Top Answer: 
    I use Apache NiFi to build workflows. It's an event that is used for distributed messaging. You need to transfer the message that comes into Kafka Broker Topic. You get the messages in the Kafka queue… more »
    Top Answer: 
    Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their… more »
    Top Answer: 
    In terms of pricing, you can't compare it to open source solutions. It would be higher compared to open source, of course, however, with the support and everything you're getting, I would say the… more »
    Top Answer: 
    With Azure specifically, the drawback is it is a very Azure-specific product. You can't connect it to external things out of Azure. For example, Spark or Databricks can be used in any cloud and can be… more »
    Ranking
    4th
    out of 14 in Compute Service
    Views
    7,615
    Comparisons
    4,260
    Reviews
    3
    Average Words per Review
    518
    Rating
    7.7
    5th
    out of 38 in Streaming Analytics
    Views
    8,022
    Comparisons
    6,978
    Reviews
    7
    Average Words per Review
    784
    Rating
    8.0
    Comparisons
    Also Known As
    ASA
    Learn More
    Overview
    Apache NiFi is an easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
    AzureStream Analytics is a fully managed event-processing engine that lets you set up real-time analytic computations on streaming data.The data can come from devices, sensors, web sites, social media feeds, applications, infrastructure systems, and more.
    Offer
    Learn more about Apache NiFi
    Learn more about Azure Stream Analytics
    Sample Customers
    Macquarie Telecom Group, Dovestech, Slovak Telekom, Looker, Hastings Group
    Rockwell Automation, Milliman, Honeywell Building Solutions, Arcoflex Automation Solutions, Real Madrid C.F., Aerocrine, Ziosk, Tacoma Public Schools, P97 Networks
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company25%
    Comms Service Provider19%
    Financial Services Firm10%
    Manufacturing Company6%
    VISITORS READING REVIEWS
    Computer Software Company29%
    Comms Service Provider20%
    Energy/Utilities Company6%
    Financial Services Firm6%
    Company Size
    No Data Available
    REVIEWERS
    Small Business29%
    Midsize Enterprise14%
    Large Enterprise57%
    Find out what your peers are saying about Amazon, Apache, Zadara and others in Compute Service. Updated: January 2022.
    564,729 professionals have used our research since 2012.

    Apache NiFi is ranked 4th in Compute Service with 3 reviews while Azure Stream Analytics is ranked 5th in Streaming Analytics with 7 reviews. Apache NiFi is rated 7.6, while Azure Stream Analytics is rated 8.0. The top reviewer of Apache NiFi writes "Open source solution that allows you to collect data with ease". On the other hand, the top reviewer of Azure Stream Analytics writes "A serverless scalable event processing engine with a valuable IoT feature". Apache NiFi is most compared with Google Cloud Dataflow, AWS Lambda, Apache Spark, Apache Storm and IBM Streams, whereas Azure Stream Analytics is most compared with Databricks, Apache Spark, Apache Flink, Apache Spark Streaming and Amazon Kinesis.

    We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.