HPE Data Fabric vs. Oracle Coherence

MapR is more well-suited for people who know what they are doing. I consider MapR the Hadoop distribution professionals use.

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Oracle Coherence can be used to solve latency problems by caching data near the application tier. In-memory performance helps to reduce data contention, thus improving application response time. Oracle Coherence does a great job at scaling linearly and can do so dynamically. Oracle Coherence can replicate data so it can be part of a disaster recovery solution. One thing that is often overlooked with elastic caches is their ability to analyze data in memory, leveraging the processing power of the data grid. This is something Oracle Coherence does exceptionally well. Oracle Coherence also provided event handling capabilities to allow applications to respond to events triggered by transactions.

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• 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.

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• Performance. Superfast resolution of complex data grid queries.
• Reliability. Availability domain support for disaster recovery.
• Programming model. Frictionless API for use with Java 8.

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• 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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• I can't really come up with too many flaws, but possibly a bit expensive considering there are good open source caches like Ehcache.

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Oracle Coherence support team is responsive and knowledgeable. We contacted them to ask a couple of design questions about how we were setting up Oracle Coherence based on how we used IBM's Datapower Extreme Scale. They were able to guide us so that we got the design correct the first time and didn't have to go back and re-architect our design later.

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I don't believe there is as much support for MapR yet compared to other more widely known products.

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DataSynapse GridServer has the same cache functionality connected with a grid distributed application deployment platform. It provides all the necessary tools to configure and manage these applications. On the otherhand Oracle Coherence has more a flexible configuration and better performance. Also the Oracle configuration and monitoring tools are more convenient and informative than the DataSynapse ones.

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• 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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• In my current project, it is yet to be decided as we are on the way to make it live for users. But I am sure it will be an added value to obtain timely calculations.

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