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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    HPE Data Fabric

    Score9.4 out of 10
    N/AHPE Data Fabric (formerly MapR, acquired by HPE in 2019) is a software-defined datastore and file system that simplifies data management and analytics by unifying data across core, edge, and multicloud sources into a single platform.N/A

    RabbitMQ

    Score9.5 out of 10
    N/ARabbitMQ, an open source message broker, is part of Pivotal Software, a VMware company acquired in 2019, and supports message queue, multiple messaging protocols, and more. RabbitMQ is available open source, however VMware also offers a range of commercial services for RabbitMQ; these are available as part of the Pivotal App Suite.N/A
    Pricing
    HPE Data FabricRabbitMQ
    Editions & Modules
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    Pricing Offerings
    HPE Data FabricRabbitMQ
    Free Trial
    NoNo
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    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    HPE Data FabricRabbitMQ
    Considered Both Products
    Hewlett Packard Enterprise (HPE)
    No answer on this topic
    Open Source
    No answer on this topic
    Key User Insights
    Would buy again
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    91%
    Would buy again
    10 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    11 Answers
    Happy with the feature set
    No answers on this topic
    91%
    Happy with the feature set
    10 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    7 Answers
    Implementation went as expected
    No answers on this topic
    100%
    Implementation went as expected
    11 Answers
    Best Alternatives
    HPE Data FabricRabbitMQ
    Small Businesses
    No answers on this topic
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    Medium-sized Companies
    HBase
    Score7.3 out of 10
    Apache Kafka
    Score8.9 out of 10
    Enterprises
    Cassandra
    Score9 out of 10
    Apache Kafka
    Score8.9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    HPE Data FabricRabbitMQ
    Likelihood to Recommend
    7.2
    (4 ratings)
    9.9
    (11 ratings)
    Usability
    -
    (0 ratings)
    8.0
    (1 ratings)
    Support Rating
    -
    (0 ratings)
    6.5
    (4 ratings)
    User Testimonials
    HPE Data FabricRabbitMQ
    Likelihood to Recommend
    Hewlett Packard Enterprise (HPE)
    MapR is more well-suited for people who know what they are doing. I consider MapR the Hadoop distribution professionals use.
    Incentivized
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    Open Source
    It is highly recommended that if you have microservices architecture and if you want to solve 2 phase commit issue, you should use RabbitMQ for communication between microservices. It is a quick and reliable mode of communication between microservices. It is also helpful if you want to implement a job and worker mechanism. You can push the jobs into RabbitMQ and that will be sent to the consumer. It is highly reliable so you won't miss any jobs and you can also implement a retry of jobs with the dead letter queue feature. It will be also helpful in time-consuming API. You can put time-consuming items into a queue so they will be processed later and your API will be quick.
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    Pros
    Hewlett Packard Enterprise (HPE)
    • MapR had very fast I/O throughput. The write speed was several times faster than what we could achieve with the other Hadoop vendors (Cloudera and Hortonworks). This is because MapR does not use HDFS, which is essentially a "meta filesystem". HDFS is built on top of the filesystem provided by the OS. MapR has their filesystem called MapR-FS, which is a true filesystem and accesses the raw disk drives.
    • The MapR filesystem is very easy to integrate with other Linux filesystems. When working with HDFS from Apache Hadoop, you usually have to use either the HDFS API or various Hadoop/HDFS command line utilities to interact with HDFS. You cannot use command line utilities native to the host operation system, which is usually Linux. At least, it is not easily done without setting up NFS, gateways, etc. With MapR-FS, you can mount the filesystem within Linux and use the standard Unix commands to manipulate files.
    • The HBase distribution provided by MapR is very similar to the Apache HBase distribution. Cloudera and Hortonworks add GUIs and other various tools on top of their HBase distributions. The MapR HBase distribution is very similar to the Apache distribution, which is nice if you are more accustomed to using Apache HBase.
    Incentivized
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    Open Source
    • What RabbitMQ does well is what it's advertised to do. It is good at providing lots of high volume, high availability queue. We've seen it handle upwards of 10 million messages in its queues, spread out over 200 queues before its publish/consume rates dipped. So yeah, it can definitely handle a lot of messages and a lot of queues. Depending on the size of the machine RabbitMQ is running on, I'm sure it can handle more.
    • Decent number of plugins! Want a plugin that gives you an interface to view all the queues and see their publish/consume rates? Yes, there's one for that. Want a plugin to "shovel" messages from one queue to another in an emergency? Check. Want a plugin that does extra logging for all the messages received? Got you covered!
    • Lots of configuration possibilities. We've tuned over 100 settings over the past year to get the performance and reliability just right. This could be a downside though--it's pretty confusing and some settings were hard to understand.
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    Cons
    Hewlett Packard Enterprise (HPE)
    • It takes time to get latest versions of Apache ecosystem tools released as it has to be adapted.
    • When you have issues related to Mapr-FS or Mapr Tables, its hard to figure them out by ourselves.
    • Sometime new ecosystem tools versions are released without proper QA.
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    Open Source
    • It breaks communication if we don't acknowledge early. In some cases our work items are time consuming that will take a time and in that scenario we are getting errors that RabbitMQ broke the channel. It will be good if RabbitMQ provides two acknowledgements, one is for that it has been received at client side and second ack is client is completed the processing part.
    Incentivized
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    Usability
    Hewlett Packard Enterprise (HPE)
    No answers on this topic
    Open Source
    RabbitMQ is very easy to configure for all supported languages (Python, Java, etc.). I have personally used it on Raspberry Pi devices via a Flask Python API as well as in Java applications. I was able to learn it quickly and now have full mastery of it. I highly recommend it for any IoT project.
    Incentivized
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    Support Rating
    Hewlett Packard Enterprise (HPE)
    No answers on this topic
    Open Source
    I gave it a 10 but we do not have a support contract with any company for RabbitMQ so there is no official support in that regard. However, there is a community and questions asked on StackOverflow or any other major question and answer site will usually get a response.
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    Alternatives Considered
    Hewlett Packard Enterprise (HPE)
    I don't believe there is as much support for MapR yet compared to other more widely known products.
    Incentivized
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    Open Source
    RabbitMQ has a few advantages over Azure Service Bus 1) RMQ handles substantially larger files - ASB tops out at 100MB, we use RabbitMQfor files over 200MB 2) RabbitMQ can be easily setup on prem - Azure Service Bus is cloud only 3) RabbitMQ exchanges are easier to configure over ASB subscriptions ASB has a few advantages too 1) Cloud based - just a few mouse clicks and you're up and running
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    Return on Investment
    Hewlett Packard Enterprise (HPE)
    • Increased employee efficiency for sure. Our clients have various levels of expertise in their deployment and user teams, and we never receive complaints about MapR.
    • MapR is used by one of our financial services clients who uses it for fraud detection and user pattern analysis. They are able to turn around data much faster than they previously had with in-house applications
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    Open Source
    • Positive: we don't need to keep way too many backend machines around to deal with bursts because RabbitMQ can absorb and buffer bursts long enough to let an understaffed set of backend services to catch up on processing. Hard to put a number to it but we probably save $5k a month having fewer machines around.
    • Negative: we've got many angry customers due to queues suddenly disappearing and dropping our messages when we try to publish to them afterward. Ideally, RabbitMQ should warn the user when queues expire due to inactivity but it doesn't, and due to our own bugs we've lost a lot of customer data as a result.
    • Positive: makes decoupling the web and API services from the deeper backend services easier by providing queues as an interface. This allowed us to split up our teams and have them develop independently of each other, speeding up software development.
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