Acoustic Analytics (formerly IBM Watson Customer Experience Analytics) vs MapR

• Tealeaf provides a unique view into a website beyond what typical web analytics can provide.
• It captures all of a website's traffic, no need to tag pages or decide ahead of time what data you want to capture.
• Data is captured and processed in real-time which reveal unknown issues as they are happening.
• Replay session to see what a customer or user actually did and not just they remember doing when a problem occured.

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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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• More knowledge sharing sessions
• UI/UX Improvements
• More tooltips on icons

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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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• The ROI question needs to be focused on clients and not our use internally. We leverage this as a platform for designing customer journeys for our clients.
• The ROI case is far easier to make for eCommerce operators. Customer journey failings can be easily quantified and seemingly simple issues can generate large ROI outcomes. For web assets without a trading bias, ROI can be established using notional value attribution. For example, a lead for motor insurance that is lost can be costed based on average policy value over a typical lifetime; struggle on a customer self-service portal can be quantified on the cost of handling through a call centre; etc.

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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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