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Databricks Data Intelligence Platform vs. HPE Data Fabric

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Databricks Data Intelligence Platform

    Score9 out of 10
    N/ADatabricks offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service provides a platform for data pipelines, data lakes, and data platforms.

    $0.07

    Per DBU

    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
    Databricks Data Intelligence PlatformHPE Data Fabric
    Editions & Modules
    Standard
    $0.07
    Per DBU
    Premium
    $0.10
    Per DBU
    Enterprise
    $0.13
    Per DBU
    No answers on this topic
    Offerings
    Pricing Offerings
    Databricks Data Intelligence PlatformHPE 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
    Community Pulse
    Databricks Data Intelligence PlatformHPE Data Fabric
    Considered Both Products
    Databricks
    No answer on this topic
    Hewlett Packard Enterprise (HPE)
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    16 Answers
    No answers on this topic
    Delivers good value for the price
    100%
    Delivers good value for the price
    16 Answers
    No answers on this topic
    Happy with the feature set
    94%
    Happy with the feature set
    15 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    10 Answers
    No answers on this topic
    Implementation went as expected
    92%
    Implementation went as expected
    12 Answers
    No answers on this topic
    Best Alternatives
    Databricks Data Intelligence PlatformHPE Data Fabric
    Small Businesses
    No answers on this topic
    No answers on this topic
    Medium-sized Companies
    SAP Business Data Cloud
    Score8.6 out of 10
    HBase
    Score7.3 out of 10
    Enterprises
    SAP Business Data Cloud
    Score8.6 out of 10
    Cassandra
    Score9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Databricks Data Intelligence PlatformHPE Data Fabric
    Likelihood to Recommend
    9.4
    (21 ratings)
    7.2
    (4 ratings)
    Usability
    9.7
    (7 ratings)
    -
    (0 ratings)
    Support Rating
    8.7
    (2 ratings)
    -
    (0 ratings)
    Contract Terms and Pricing Model
    8.0
    (1 ratings)
    -
    (0 ratings)
    Professional Services
    10.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Databricks Data Intelligence PlatformHPE Data Fabric
    Likelihood to Recommend
    Databricks
    Medium to Large data throughput shops will benefit the most from Databricks Spark processing. Smaller use cases may find the barrier to entry a bit too high for casual use cases. Some of the overhead to kicking off a Spark compute job can actually lead to your workloads taking longer, but past a certain point the performance returns cannot be beat.
    Incentivized
    Read full review
    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
    Databricks
    • Process raw data in One Lake (S3) env to relational tables and views
    • Share notebooks with our business analysts so that they can use the queries and generate value out of the data
    • Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
    • Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers
    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
    Databricks
    • Sometimes, when multiple jobs depend on each other in different environments, it is not always easy to see the full workflow in one place.
    • It is sometimes difficult to determine which job or cluster contributes more to the overall cost.
    • For beginners, cluster configuration may be a little difficult. So more recommendation in the platform can help.
    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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    Usability
    Databricks
    Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

    in terms of graph generation and interaction it could improve their UI and UX
    Incentivized
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    Hewlett Packard Enterprise (HPE)
    No answers on this topic
    Support Rating
    Databricks
    One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
    Read full review
    Hewlett Packard Enterprise (HPE)
    No answers on this topic
    Alternatives Considered
    Databricks
    The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when it comes to Spark Job Execution. Other platforms need to be self-managed, which is another huge hassle.
    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
    Databricks
    • The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
    • DB has the ability to terminate/time out instances which helps manage cost.
    • The ability to quickly access typical hard to build data scenarios easily is a strength.
    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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