HPE Data Fabric vs. Talend Data Fabric

If you need Hadoop and just need raw speed for I/O and have a Hadoop savvy group of engineers who don't need/like web UIs, then MapR is a great fit for you. If you are new to Hadoop or have DevOps folks that are not Hadoop gurus, choosing MapR as your Hadoop vendor will have a steeper learning curve as you will need to do more training and build more admin consoles for them.

Incentivized

The best scenario that I see as productive is having several sources of information, the tool allows me to consolidate in a single income channel allowing me to maintain the integrity of the information, I like the treatment of financial data since speed and accuracy are needed in the accounting records. I believe that in any industry this tool would be 100% productive.

Incentivized

• MapR allows easy integration with HBase and MapR DB.
• Easy trial server setup for product testing.
• Excellent training program to help new users get up-to-date with MapR and related products.

Incentivized

• It supports a wide variety of connectors (Systems/endpoints)
• It provides great flexibility for developers as it not only has a lot of predefined ready to use the function but also provides the ability to use complex java code within the platform. Great tool if you have good developers available.

Incentivized

• I think MapR's main problem is name recognition. Hortonworks and Cloudera both are big names in the industry, but their deployment mechanisms are a little more difficult to use, especially when trying to fully automate it's deployment.
• Documentation could always be better. But really, if that's your main weakness, it's everybody's weakness.

Incentivized

• Bugs: Came across some of the bugs in transforming column datatype especially on text.
• Speed: Sometimes, bandwidth fluctuates in the data transfer as identified from logs, but so far so good.
• Connector support: So far have not seen Actian Matrix plugins, could be useful.

Incentivized

Lack of report export and publication! Steep learning curve!

At this moment the usability of Talend Data Quality is optimal, too bad I cannot say the same in the first three months, it was always a problem due to its steep learning curve, but what matters is being able to use it effectively at this precise moment.

Incentivized

Talend Data Quality gave us direct help in the learning process and prevented us from taking many more months to adapt and I appreciate this from the heart, I think that thanks to the support we can have very detailed reports that help increase the use of Talend Data Quality in the company.

Incentivized

Hortonworks and Cloudera are both sort of hacky. We have to do a lot of extra steps to automate those two. MapR has far fewer issues and doesn't force you into a once size fits all deployment scenario. There are multiple ways to deploy and some are more amenable to automation, MapR just has that in spades

Incentivized

1) Talend offers more than 200 palettes, but most of them are repeated. For Example in Pentaho, we can use a single component ( Microsoft Excel input ) and we can get the data, sheet name, file name, and all other things like using a wildcard, etc. 2. Talend is an open-source tool that makes it easily accessible.

Incentivized

• Less manual intervention for maintaining a cluster.

Incentivized

• The steep learning curve negatively impacts ROI during the first few months.
• After solving the difficulties with learning Talend Data Quality, we can achieve an increase in ROI with accurate and visually appealing reports.
• Integration with Salesforce is another positive breakthrough in ROI.

Incentivized