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Azure Stream Analytics vs Databricks comparison

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Azure Stream Analytics Logo
8,022 views|6,978 comparisons
Databricks Logo
30,779 views|25,469 comparisons
Featured Review
Find out what your peers are saying about Azure Stream Analytics vs. Databricks and other solutions. Updated: January 2022.
564,599 professionals have used our research since 2012.
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"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.""I like the IoT part. We have mostly used Azure Stream Analytics services for it""Provides deep integration with other Azure resources.""The most valuable features are the IoT hub and the Blob storage.""Technical support is pretty helpful.""Real-time analytics is the most valuable feature of this solution. I can send the collected data to Power BI in real time.""The solution has a lot of functionality that can be pushed out to companies."

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"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes.""The technical support is good.""It's easy to increase performance as required.""The main features of the solution are efficiency.""Databricks is a scalable solution. It is the largest advantage of the solution.""Databricks gives you the flexibility of using several programming languages independently or in combination to build models.""The solution is very easy to use.""Imageflow is a visual tool that helps make it easier for business people to understand complex workflows."

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Cons
"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.""The collection and analysis of historical data could be better.""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.""Early in the process, we had some issues with stability.""The solution offers a free trial, however, it is too short.""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."

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"Pricing is one of the things that could be improved.""There should be better integration with other platforms.""The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good.""Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively.""Overall it's a good product, however, it doesn't do well against any individual best-of-breed products.""Would be helpful to have additional licensing options.""It's not easy to use, and they need a better UI.""Costs can quickly add up if you don't plan for it."

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Pricing and Cost Advice
  • "The cost of this solution is less than competitors such as Amazon or Google Cloud."
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  • "Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
  • "We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
  • "The pricing depends on the usage itself."
  • "I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
  • "The price is okay. It's competitive."
  • "Databricks uses a price-per-use model, where you can use as much compute as you need."
  • "There are different versions."
  • "The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."
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    Questions from the Community
    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 »
    Top Answer: 
    Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with… more »
    Top Answer: 
    We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It… more »
    Top Answer: 
    The initial setup is pretty easy.
    Ranking
    5th
    out of 38 in Streaming Analytics
    Views
    8,022
    Comparisons
    6,978
    Reviews
    7
    Average Words per Review
    784
    Rating
    8.0
    1st
    out of 38 in Streaming Analytics
    Views
    30,779
    Comparisons
    25,469
    Reviews
    22
    Average Words per Review
    531
    Rating
    7.9
    Comparisons
    Also Known As
    ASA
    Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
    Learn More
    Overview
    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.

    Databricks creates a Unified Analytics Platform that accelerates innovation by unifying data science, engineering, and business. It utilizes Apache Spark to help clients with cloud-based big data processing. It puts Spark on “autopilot” to significantly reduce operational complexity and management cost. The Databricks I/O module (DBIO) improves the read and write performance of Apache Spark in the cloud. An increase in productivity is ensured through Databricks’ collaborative workplace.

    Offer
    Learn more about Azure Stream Analytics
    Learn more about Databricks
    Sample Customers
    Rockwell Automation, Milliman, Honeywell Building Solutions, Arcoflex Automation Solutions, Real Madrid C.F., Aerocrine, Ziosk, Tacoma Public Schools, P97 Networks
    Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company29%
    Comms Service Provider20%
    Energy/Utilities Company6%
    Financial Services Firm6%
    REVIEWERS
    Financial Services Firm14%
    Computer Software Company14%
    Mining And Metals Company14%
    Energy/Utilities Company7%
    VISITORS READING REVIEWS
    Computer Software Company27%
    Comms Service Provider15%
    Financial Services Firm8%
    Government5%
    Company Size
    REVIEWERS
    Small Business29%
    Midsize Enterprise14%
    Large Enterprise57%
    REVIEWERS
    Small Business14%
    Midsize Enterprise17%
    Large Enterprise69%
    VISITORS READING REVIEWS
    Small Business26%
    Midsize Enterprise19%
    Large Enterprise55%
    Find out what your peers are saying about Azure Stream Analytics vs. Databricks and other solutions. Updated: January 2022.
    564,599 professionals have used our research since 2012.

    Azure Stream Analytics is ranked 5th in Streaming Analytics with 7 reviews while Databricks is ranked 1st in Streaming Analytics with 23 reviews. Azure Stream Analytics is rated 8.0, while Databricks is rated 7.8. The top reviewer of Azure Stream Analytics writes "A serverless scalable event processing engine with a valuable IoT feature". On the other hand, the top reviewer of Databricks writes "Has a good feature set but it needs samples and templates to help invite users to see results". Azure Stream Analytics is most compared with Apache Spark, Apache Flink, Apache Spark Streaming, Apache NiFi and Amazon Kinesis, whereas Databricks is most compared with Microsoft Azure Machine Learning Studio, Amazon SageMaker, Alteryx, Dataiku Data Science Studio and Google Cloud Datalab. See our Azure Stream Analytics vs. Databricks report.

    See our list of best Streaming Analytics vendors.

    We monitor all Streaming Analytics 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.