TrustRadius: an HG Insights company

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Augury

    N/AN/AAugury provides solutions that help eliminate production downtime, improve process efficiency, maximize yield and reduce waste and emissions, offering customers with prescriptive insights into their processes and machines through AI-driven technology and industry-specific expertise that helps transform how they work.N/A

    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
    Pricing
    AuguryHPE Data Fabric
    Editions & Modules
    No answers on this topic
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    Offerings
    Pricing Offerings
    AuguryHPE Data Fabric
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details
    More Pricing Information
    Best Alternatives
    AuguryHPE Data Fabric
    Small Businesses
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    Medium-sized Companies
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    HBase
    Score7.3 out of 10
    Enterprises
    No answers on this topic
    Cassandra
    Score9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    AuguryHPE Data Fabric
    Likelihood to Recommend
    -
    (0 ratings)
    7.2
    (4 ratings)
    User Testimonials
    AuguryHPE Data Fabric
    Likelihood to Recommend
    Augury Inc
    No answers on this topic
    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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    Pros
    Augury Inc
    No answers on this topic
    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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    Cons
    Augury Inc
    No answers on this topic
    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.
    Incentivized
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    Alternatives Considered
    Augury Inc
    No answers on this topic
    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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    Return on Investment
    Augury Inc
    No answers on this topic
    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
    Incentivized
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