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Google Cloud IoT vs. Hitachi Lumada vs. HPE Data Fabric

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Google Cloud IoT

    Score8.6 out of 10
    N/AThe Google Cloud IoT Core is a fully managed service that allows you to easily and securely connect, manage, and ingest data from millions of globally dispersed devices. Cloud IoT Core, in combination with other services on Cloud IoT platform, provides a complete solution for collecting, processing, analyzing, and visualizing IoT data in real time to support improved operational efficiency.N/A

    Hitachi Lumada

    Score8.5 out of 10
    N/AHitachi Vantara offers Hitachi Lumada, an Internet of Things management and analytics platform.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
    Google Cloud IoTHitachi LumadaHPE Data Fabric
    Editions & Modules
    No answers on this topic
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Google Cloud IoTHitachi LumadaHPE Data Fabric
    Free Trial
    NoNoNo
    Free/Freemium Version
    NoNoNo
    Premium Consulting/Integration Services
    NoNoNo
    Entry-level Setup FeeNo setup feeNo setup feeNo setup fee
    Additional Details———
    More Pricing Information
    Features
    Google Cloud IoTHitachi LumadaHPE Data Fabric
    Internet of Things
    Comparison of Internet of Things features of Google Cloud IoT and Hitachi Lumada and HPE Data Fabric
    Feature
    Google Cloud IoT
    6.9
    2 Ratings
    14% below category average
    Hitachi Lumada
    -
    Ratings
    HPE Data Fabric
    -
    Ratings
    IoT Device Management5.22 Ratings00 Ratings00 Ratings
    Device Security9.01 Ratings00 Ratings00 Ratings
    IoT Data Management7.52 Ratings00 Ratings00 Ratings
    IoT Analytics7.52 Ratings00 Ratings00 Ratings
    IoT Integration5.42 Ratings00 Ratings00 Ratings
    Best Alternatives
    Google Cloud IoTHitachi LumadaHPE Data Fabric
    Small Businesses
    AWS IoT Core
    Score10 out of 10
    No answers on this topic
    No answers on this topic
    Medium-sized Companies
    No answers on this topic
    No answers on this topic
    HBase
    Score7.3 out of 10
    Enterprises
    AWS IoT Core
    Score10 out of 10
    No answers on this topic
    Cassandra
    Score9 out of 10
    All AlternativesView all alternativesView all alternativesView all alternatives
    User Ratings
    Google Cloud IoTHitachi LumadaHPE Data Fabric
    Likelihood to Recommend
    6.3
    (2 ratings)
    8.5
    (2 ratings)
    7.2
    (4 ratings)
    User Testimonials
    Google Cloud IoTHitachi LumadaHPE Data Fabric
    Likelihood to Recommend
    Google
    I consider myself very techy and found Google Cloud IoT platform very challenging to manage. The lack of tutorials and discussions to understand how each section works is very challenging. I specifically made a connection after several hours to Google Nest to third-party integration, Home Assistant. Shortly after Google Cloud upgraded to a new version breaking the connection. This was extremely frustrating. No service should take several hours to figure out, in my opinion, if it does, the platform is doing a poor job of making it easy. I'm personally very discouraged any time I ever have to use this platform. It's very hard to find answers.
    Incentivized
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    Hitachi Vantara
    Organizations may use sensors like RFID and break beams to automatically monitor components as they travel through the assembly. Real-time data from IoT may help managers and supervisors monitor the performance of their teams. With this level of transparency, bottlenecks can be identified, problems can be pinpointed, and progress can be made more quickly.
    Incentivized
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    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
    Google
    • Integration with different brands of microcontrollers including the one currently used by Espresiff.
    • The platform is very robust and secure.
    Incentivized
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    Hitachi Vantara
    • Improve business process outcomes.
    • Improve business process agility.
    • Drive innovation, cost management, and revenue growth.
    Incentivized
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    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
    Google
    • Not beginner friendly.
    • Needs more tutorials and walk throughs on how to get started.
    • Very complicated and unless you know what you are doing you will be lost.
    • Lack of material found on how to do each section / services.
    Incentivized
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    Hitachi Vantara
    • Data security can be improved.
    • Adoption flexibility.
    • Steep learning curve.
    Incentivized
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    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
    Google
    Although comparisons are hateful, even more so when we are talking about leading brands where the quality of their services are indisputable, the general environment of Google was more familiar to me since I use, for example, Google Firebase on a daily basis, where part of the concepts are similar, without Without a doubt, AWS services are excellent, but it was easier for me to go through the functions of Google Cloud IoT.
    Incentivized
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    Hitachi Vantara
    A lot of components are available and able to use what you need. Module library, Advanced analytics. Batch data processing. Variety of ways to integrate. Cost-effective. These are some of the ways Hitachi Lumada ranks above the ones we have used.
    Incentivized
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    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
    Google
    • The amount of hours to get things integrated is negative.
    • The amount of hours researching how to get devices integrated is negative.
    • Overall the amount of time and effort getting things working has been a negative experience.
    Incentivized
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    Hitachi Vantara
    • Overall cost.
    • Financial/organizational viability.
    • Strong services expertise.
    Incentivized
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    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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