Apache Kafka vs. HPE Ezmeral Data Fabric (MapR)

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Kafka
Score 8.4 out of 10
N/A
Apache Kafka is an open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java. The Kafka event streaming platform is used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.N/A
HPE Ezmeral Data Fabric (MapR)
Score 9.4 out of 10
N/A
HPE Ezmeral 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. Just as a loom weaves multiple threads into a single piece of fabric, HPE Ezmeral Data Fabric weaves distributed data into a single enterprise-wide data layer that ingests, processes, and stores data once and then makes it available for reuse across multiple…N/A
Pricing
Apache KafkaHPE Ezmeral Data Fabric (MapR)
Editions & Modules
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Offerings
Pricing Offerings
Apache KafkaHPE Ezmeral Data Fabric (MapR)
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
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Community Pulse
Apache KafkaHPE Ezmeral Data Fabric (MapR)
Top Pros
Top Cons
Best Alternatives
Apache KafkaHPE Ezmeral Data Fabric (MapR)
Small Businesses

No answers on this topic

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Medium-sized Companies
IBM MQ
IBM MQ
Score 9.0 out of 10
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Enterprises
IBM MQ
IBM MQ
Score 9.0 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 8.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache KafkaHPE Ezmeral Data Fabric (MapR)
Likelihood to Recommend
8.3
(18 ratings)
7.2
(4 ratings)
Likelihood to Renew
9.0
(2 ratings)
-
(0 ratings)
Usability
10.0
(1 ratings)
-
(0 ratings)
Support Rating
8.4
(4 ratings)
-
(0 ratings)
User Testimonials
Apache KafkaHPE Ezmeral Data Fabric (MapR)
Likelihood to Recommend
Apache
Apache Kafka is well-suited for most data-streaming use cases. Amazon Kinesis and Azure EventHubs, unless you have a specific use case where using those cloud PaAS for your data lakes, once set up well, Apache Kafka will take care of everything else in the background. Azure EventHubs, is good for cross-cloud use cases, and Amazon Kinesis - I have no real-world experience. But I believe it is the same.
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Hewlett Packard Enterprise
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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Pros
Apache
  • Really easy to configure. I've used other message brokers such as RabbitMQ and compared to them, Kafka's configurations are very easy to understand and tweak.
  • Very scalable: easily configured to run on multiple nodes allowing for ease of parallelism (assuming your queues/topics don't have to be consumed in the exact same order the messages were delivered)
  • Not exactly a feature, but I trust Kafka will be around for at least another decade because active development has continued to be strong and there's a lot of financial backing from Confluent and LinkedIn, and probably many other companies who are using it (which, anecdotally, is many).
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Hewlett Packard Enterprise
  • 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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Cons
Apache
  • Sometimes it becomes difficult to monitor our Kafka deployments. We've been able to overcome it largely using AWS MSK, a managed service for Apache Kafka, but a separate monitoring dashboard would have been great.
  • Simplify the process for local deployment of Kafka and provide a user interface to get visibility into the different topics and the messages being processed.
  • Learning curve around creation of broker and topics could be simplified
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Hewlett Packard Enterprise
  • 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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Likelihood to Renew
Apache
Kafka is quickly becoming core product of the organization, indeed it is replacing older messaging systems. No better alternatives found yet
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Hewlett Packard Enterprise
No answers on this topic
Usability
Apache
Apache Kafka is highly recommended to develop loosely coupled, real-time processing applications. Also, Apache Kafka provides property based configuration. Producer, Consumer and broker contain their own separate property file
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Hewlett Packard Enterprise
No answers on this topic
Support Rating
Apache
Support for Apache Kafka (if willing to pay) is available from Confluent that includes the same time that created Kafka at Linkedin so they know this software in and out. Moreover, Apache Kafka is well known and best practices documents and deployment scenarios are easily available for download. For example, from eBay, Linkedin, Uber, and NYTimes.
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Hewlett Packard Enterprise
No answers on this topic
Alternatives Considered
Apache
I used other messaging/queue solutions that are a lot more basic than Confluent Kafka, as well as another solution that is no longer in the market called Xively, which was bought and "buried" by Google. In comparison, these solutions offer way fewer functionalities and respond to other needs.
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Hewlett Packard Enterprise
I don't believe there is as much support for MapR yet compared to other more widely known products.
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Return on Investment
Apache
  • Positive: Get a quick and reliable pub/sub model implemented - data across components flows easily.
  • Positive: it's scalable so we can develop small and scale for real-world scenarios
  • Negative: it's easy to get into a confusing situation if you are not experienced yet or something strange has happened (rare, but it does). Troubleshooting such situations can take time and effort.
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Hewlett Packard Enterprise
  • 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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