The Cloudera Enterprise Data Hub powered by SDX is a multifunction analytics solution that supports a range of operational and analytic use cases for enterprises.
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HPE Data Fabric
Score 9.4 out of 10
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HPE 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.
We only evaluated but never implemented Vertica since apart from poor customer support we noticed that it also missed some data warehouse capabilities that would suit our needs.
Cloudera is a
great choice because it provides fast streaming data for tracking, breaks down
silos by providing unified self-service platforms for data-driven insights,
Cloudera is
compatible with Windows operating systems, and Mac allows cloud-based
deployment, it is also very useful to configure data encryption, guarantee
Cloudera supports Impala and Hortonworks supports LLAP and both of them are good in terms of performance. Hortonworks uses more up to date technology support in terms of supported versions.
It was the first and best Hadoop distribution when we started years ago. But the situation changed now and if given a choice, may end up choosing something else.
It was selected for lab testing and definitely have positive experience.
Verified User
Anonymous
Chose Cloudera Enterprise Data Hub
I have used Amazon Elastic Cloud Compute EC2, Windows Azure. But the difference with these products and Cloudera is Amazon and Azure are more costly. But Cloudera is best because of Data sensitivity and privacy. We have all the shareholder activity data for funds that business …
Sr. Development Engineer - Big Data Platform Architecture
Chose Cloudera Enterprise Data Hub
NA
Verified User
Anonymous
Chose Cloudera Enterprise Data Hub
A deep bench of Hadoop experts, major contributions to the Hadoop open source community and a solid head start getting market recognition, skills and awareness across the teams.
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, …
When we were shopping, Mapr had the momentum, high availability even on Hadoop 1.x, an improved file system and better a central control system. Now it looks like the situation has changed a lot.
We supported all three Hadoop vendors with our Hadoop RDBMS product. Here's how I see the commercial Hadoop distribution world. If you need raw performance and don't mind proprietary technology, go with MapR. If you care about the most pure open source, go with Hortonworks. If …
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.
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.
Likely to renew the use in case the requirements for Cloudera remain valid. The rapid change in customer requirements and solutions that must be validated, integrated or tested changes. As the maturity of the solution increases, the requirements to renew use decrease. From a solution feature perspective by itself would probably grade 10.
Cloudera is a great choice because it provides fast streaming data for tracking, breaks down silos by providing unified self-service platforms for data-driven insights, secures machine learning, AI solutions, and stores self-service data, enabling our analysts to concentrate on more important tasks like displaying critical information.
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
Cloudera products are the most widely. It is more business friendly as data is more secure. The sensitive data that you operate on is local to you and your project rather than processing this data on Cloud.
Cloudera is definitely faster as wait time is reduced if on Cloud.
A lot range of products are covered. So it is definitely good for businesses and had good returns on investments.