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HPE Data Fabric vs. Oracle Autonomous Data Warehouse

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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

    Oracle Autonomous Data Warehouse

    Score8.1 out of 10
    N/AOracle Autonomous Data Warehouse is optimized for analytic workloads, including data marts, data warehouses, data lakes, and data lakehouses. With Autonomous Data Warehouse, data scientists, business analysts, and nonexperts can discover business insights using data of any size and type. The solution is built for the cloud and optimized using Oracle Exadata.N/A
    Pricing
    HPE Data FabricOracle Autonomous Data Warehouse
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    HPE Data FabricOracle Autonomous Data Warehouse
    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
    Community Pulse
    HPE Data FabricOracle Autonomous Data Warehouse
    Considered Both Products
    Hewlett Packard Enterprise (HPE)
    No answer on this topic
    Oracle
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    100%
    Would buy again
    7 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    6 Answers
    Happy with the feature set
    No answers on this topic
    100%
    Happy with the feature set
    7 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    5 Answers
    Implementation went as expected
    No answers on this topic
    100%
    Implementation went as expected
    7 Answers
    Best Alternatives
    HPE Data FabricOracle Autonomous Data Warehouse
    Small Businesses
    No answers on this topic
    No answers on this topic
    Medium-sized Companies
    HBase
    Score7.3 out of 10
    Cloudera Enterprise Data Hub
    Score9 out of 10
    Enterprises
    Cassandra
    Score9 out of 10
    Oracle Exadata
    Score9.8 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    HPE Data FabricOracle Autonomous Data Warehouse
    Likelihood to Recommend
    7.2
    (4 ratings)
    8.9
    (32 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    8.0
    (1 ratings)
    Implementation Rating
    -
    (0 ratings)
    9.0
    (1 ratings)
    User Testimonials
    HPE Data FabricOracle Autonomous Data Warehouse
    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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    Oracle
    II would recommend Oracle Autonomous Data Warehouse to someone looking to fully automate the transferring of data especially in a warehouse scenario though I can see the elasticity of the suite that is offered and can see it is applicable in other scenarios not just warehouses.
    Incentivized
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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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    Oracle
    • Very easy and fast to load data into the Oracle Autonomous Data Warehouse
    • Exceptionally fast retrieval of data joining 100 million row table with a billion row table plus the size of the database was reduced by a factor of 10 due to how Oracle store[s] and organise[s] data and indexes.
    • Flexibility with scaling up and down CPU on the fly when needed, and just stop it when not needed so you don't get charged when it is not running.
    • It is always patched and always available and you can add storage dynamically as you need it.
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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.
    Incentivized
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    Oracle
    • It is very expensive product. But not to mention, there's good reasons why it is expensive.
    • The product should support more cloud based services. When we made the decision to buy the product (which was 20 years ago,) there was no such thing to consider, but moving to a cloud based data warehouse may promise more scalability, agility, and cost reduction. The new version of Data Warehouse came out on the way, but it looks a bit behind compared to other competitors.
    • Our healthcare data consists of 30% coded data (such as ICD 10 / SNOMED C,T) but the rests is narrative (such as clinical notes.). Oracle is the best for warehousing standardized data, but not a good choice when considering unstructured data, or a mix of the two.
    Incentivized
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    Likelihood to Renew
    Hewlett Packard Enterprise (HPE)
    No answers on this topic
    Oracle
    Because
    • It is really simple to provision and configure.
    • Does not require continous attention from the DBA, autonomous features allows the database to perform most of the regular admin tasks without need for human intervention.
    • Allows to integrate multiple data sources on a central data warehouse, and explode the information stored with different analytic and reporting tools.
    Incentivized
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    Implementation Rating
    Hewlett Packard Enterprise (HPE)
    No answers on this topic
    Oracle
    Understanding Oracle Cloud Infrastructure is really simple, and Autonomous databases are even more. Using shared or dedicated infrastructure is one of the few things you need to consider at the moment of starting provisioning your Oracle Autonomous Data Warehouse.
    Incentivized
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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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    Oracle
    As I mentioned, I have also worked with Amazon Redshift, but it is not as versatile as Oracle Autonomous Data Warehouse and does not provide a large variety of products. Oracle Autonomous Data Warehouse is also more reliable than Amazon Redshift, hence why I have chosen it
    Incentivized
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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
    Incentivized
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    Oracle
    • Overall the business objective of all of our clients have been met positively with Oracle Data Warehouse. All of the required analysis the users were able to successfully carry out using the warehouse data.
    • Using a 3-tier architecture with the Oracle Data Warehouse at the back end the mid-tier has been integrated well. This is big plus in providing the necessary tools for end users of the data warehouse to carry out their analysis.
    • All of the various BI products (OBIEE, Cognos, etc.) are able to use and exploit the various analytic built-in functionalities of the Oracle Data Warehouse.
    Incentivized
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