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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Hadoop

    Score7.5 out of 10
    N/AHadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.N/A

    AWS Lambda

    Score8.3 out of 10
    N/AAWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to run and scale code with high availability.

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    Pricing
    HadoopAWS Lambda
    Editions & Modules
    No answers on this topic
    128 MB
    $0.0000000021
    Per 1 ms
    1024 MB
    $0.0000000167
    Per 1 ms
    10240 MB
    $0.0000001667
    Per 1 ms
    Offerings
    Pricing Offerings
    HadoopAWS Lambda
    Free Trial
    NoNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details
    More Pricing Information
    Features
    HadoopAWS Lambda
    Access Control and Security
    Comparison of Access Control and Security features of Apache Hadoop and AWS Lambda
    Feature
    Apache Hadoop
    -
    Ratings
    AWS Lambda
    8.8
    7 Ratings
    4% above category average
    Multiple Access Permission Levels (Create, Read, Delete)00 Ratings8.57 Ratings
    Single Sign-On (SSO)00 Ratings9.03 Ratings
    Reporting & Analytics
    Comparison of Reporting & Analytics features of Apache Hadoop and AWS Lambda
    Feature
    Apache Hadoop
    -
    Ratings
    AWS Lambda
    4.9
    6 Ratings
    29% below category average
    Dashboards00 Ratings5.46 Ratings
    Standard reports00 Ratings5.05 Ratings
    Custom reports00 Ratings4.35 Ratings
    Function as a Service (FaaS)
    Comparison of Function as a Service (FaaS) features of Apache Hadoop and AWS Lambda
    Feature
    Apache Hadoop
    -
    Ratings
    AWS Lambda
    8.8
    7 Ratings
    5% above category average
    Programming Language Diversity00 Ratings9.07 Ratings
    Runtime API Authoring00 Ratings8.07 Ratings
    Function/Database Integration00 Ratings9.07 Ratings
    DevOps Stack Integration00 Ratings9.17 Ratings
    Best Alternatives
    HadoopAWS Lambda
    Small Businesses
    No answers on this topic
    IBM Cloud Functions
    Score6.5 out of 10
    Medium-sized Companies
    Cloudera Manager (no longer available standalone)
    Score9.9 out of 10
    IBM Cloud Functions
    Score6.5 out of 10
    Enterprises
    Amazon EMR
    Score9.1 out of 10
    IBM Cloud Functions
    Score6.5 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    HadoopAWS Lambda
    Likelihood to Recommend
    8.0
    (37 ratings)
    7.5
    (52 ratings)
    Likelihood to Renew
    9.6
    (8 ratings)
    -
    (0 ratings)
    Usability
    8.0
    (6 ratings)
    8.3
    (17 ratings)
    Performance
    8.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    7.5
    (3 ratings)
    8.7
    (20 ratings)
    Online Training
    6.1
    (2 ratings)
    -
    (0 ratings)
    Data Sharing and Collaboration
    7.7
    (10 ratings)
    -
    (0 ratings)
    Data Sources
    8.7
    (10 ratings)
    -
    (0 ratings)
    User Testimonials
    HadoopAWS Lambda
    Likelihood to Recommend
    Apache
    Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
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    Amazon AWS
    Lambda excels at event-driven, short-lived tasks, such as processing files or building simple APIs. However, it's less ideal for long-running, computationally intensive, or applications that rely on carrying the state between jobs. Cold starts and constant load can easily balloon the costs.
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    Pros
    Apache
    • Handles large amounts of unstructured data well, for business level purposes
    • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
    • Decent for large ETL pipelines and logging free-for-alls because of this, also.
    Incentivized
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    Amazon AWS
    • No provisioning required - we don't have to pay anything upfront
    • Serverless deployment - it gets executed only when request comes and we pay only for the time the request is getting executed
    • Integrates well with AWS CloudWatch triggers so it is easy to setup scheduled tasks like cron jobs
    Incentivized
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    Cons
    Apache
    • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
    • Not for small data sets
    • Data security needs to be ramped up
    • Failure in NameNode has no replication which takes a lot of time to recover
    Incentivized
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    Amazon AWS
    • Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
    • For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
    • Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
    • Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.
    Incentivized
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    Likelihood to Renew
    Apache
    Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
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    Amazon AWS
    No answers on this topic
    Usability
    Apache
    As Hadoop enterprise licensed version is quite fine tuned and easy to use makes it good choice for Hadoop administrators. It’s scalability and integration with Kerberos is good option for authentication and authorisation. installation can be improved. logging can be improved so that it become easier for debugging purposes. parallel processing of data is achieved easily.
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    Amazon AWS
    I give it a seven is usability because it's AWS. Their UI's are always clunkier than the competition and their documentation is rather cumbersome. There's SO MUCH to dig through and it's a gamble if you actually end up finding the corresponding info if it will actually help. Like I said before, going to google with a specific problem is likely a better route because AWS is quite ubiquitous and chances are you're not the first to encounter the problem. That being said, using SAM (Serverless application model) and it's SAM Local environment makes running local instances of your Lambdas in dev environments painless and quite fun. Using Nodejs + Lambda + SAM Local + VS Code debugger = AWESOME.
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    Support Rating
    Apache
    It's a great value for what you pay, and most Data Base Administrators (DBAs) can walk in and use it without substantial training. I tend to dabble on the analyst side, so querying the data I need feels like it can take forever, especially on higher traffic days like Monday.
    Incentivized
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    Amazon AWS
    Amazon consistently provides comprehensive and easy-to-parse documentation of all AWS features and services. Most development team members find what they need with a quick internet search of the AWS documentation available online. If you need advanced support, though, you might need to engage an AWS engineer, and that could be an unexpected (or unwelcome) expense.
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    Online Training
    Apache
    Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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    Amazon AWS
    No answers on this topic
    Alternatives Considered
    Apache
    Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
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    Amazon AWS
    AWS Lambda is good for short running functions, and ideally in response to events within AWS. Google App Engine is a more robust environment which can have complex code running for long periods of time, and across more than one instance of hardware. Google App Engine allows for both front-end and back-end infrastructure, while AWS Lambda is only for small back-end functions
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    Return on Investment
    Apache
    • There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
    • Hadoop is quite interesting due to its new and improved features plus innovative functions.
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    Amazon AWS
    • Positive - Only paying for when code is run, unlike virtual machines where you pay always regardless of processing power usage.
    • Positive - Scalability and accommodating larger amounts of demand is much cheaper. Instead of scaling up virtual machines and increasing the prices you pay for that, you are just increasing the number of times your lambda function is run.
    • Negative - Debugging/troubleshooting, and developing for lambda functions take a bit more time to get used to, and migrating code from virtual machines and normal processes to Lambda functions can take a bit of time.
    Incentivized
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