Apache Hive is database/data warehouse software that supports data querying and analysis of large datasets stored in the Hadoop distributed file system (HDFS) and other compatible systems, and is distributed under an open source license.
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Cloudera Enterprise Data Hub
Score 9.0 out of 10
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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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Oracle Autonomous Data Warehouse
Score 8.2 out of 10
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Oracle Autonomous Data Warehouse is optimized for analytic workloads, including data marts, data warehouses, data lakes, and data lakehouses. With Autonomous Data Warehouse, data scientists, business analysts, and nonexperts can discover business insights using data of any size and type. The solution is built for the cloud and optimized using Oracle Exadata.
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Pricing
Apache Hive
Cloudera Enterprise Data Hub
Oracle Autonomous Data Warehouse
Editions & Modules
No answers on this topic
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache Hive
Cloudera Enterprise Data Hub
Oracle Autonomous Data Warehouse
Free Trial
No
No
No
Free/Freemium Version
No
Yes
No
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Apache Hive
Cloudera Enterprise Data Hub
Oracle Autonomous Data Warehouse
Considered Multiple Products
Apache Hive
No answer on this topic
Cloudera Enterprise Data Hub
Verified User
Engineer
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 …
Hadoop still being a naive field, we have very few expertise with great knowledge in Hadoop. Oracle Data Warehouse does not support unstructured data, where as Hadoop does. There are a lot of functionalities which Oracle Data Warehouse provides, which makes us us not to go for H…
Oracle Data Warehouse became immediate selection whenever we were implementing BI solutions with Dimension Modeling and Oracle based Transactional Systems, compared to other places where we used Teradata and Netezza with 3NF model structure for BI solutions. For other various …
Software work execution is on a large scale, it is good to use for new projects or organizational changes, data lineage mapping has always been dubious but this one has had good results. You can store and synchronize data from different departments, the storage process can be manual but it is best automated.
Cloudera excels at seamless migrations and upgrades.
Cloudera supports self-healing and data center replacement of failed cloud instances while maintaining the state.
Cloudera is essential to increase or decrease capacity through the user interface or API.
Cloudera is great at simplifying big data analytics by providing the technology and tools needed to gain insights from IoT and connected devices to help monitor and condition our assets.
Cloudera's cybersecurity platform option offers stronger anomaly detection, visibility, and prevention, as well as faster behavioral analysis.
Cloudera is beneficial for enabling and utilizing the platform's machine learning and ad-hoc queries while securely storing, retrieving, and analyzing any volume of data at scale.
II would recommend Oracle Autonomous Data Warehouse to someone looking to fully automate the transferring of data especially in a warehouse scenario though I can see the elasticity of the suite that is offered and can see it is applicable in other scenarios not just warehouses.
Apache Hive allows use to write expressive solutions to complex problems thanks to its SQL-like syntax.
Relatively easy to set up and start using.
Very little ramp-up to start using the actual product, documentation is very thorough, there is an active community, and the code base is constantly being improved.
Very easy and fast to load data into the Oracle Autonomous Data Warehouse
Exceptionally fast retrieval of data joining 100 million row table with a billion row table plus the size of the database was reduced by a factor of 10 due to how Oracle store[s] and organise[s] data and indexes.
Flexibility with scaling up and down CPU on the fly when needed, and just stop it when not needed so you don't get charged when it is not running.
It is always patched and always available and you can add storage dynamically as you need it.
It is very expensive product. But not to mention, there's good reasons why it is expensive.
The product should support more cloud based services. When we made the decision to buy the product (which was 20 years ago,) there was no such thing to consider, but moving to a cloud based data warehouse may promise more scalability, agility, and cost reduction. The new version of Data Warehouse came out on the way, but it looks a bit behind compared to other competitors.
Our healthcare data consists of 30% coded data (such as ICD 10 / SNOMED C,T) but the rests is narrative (such as clinical notes.). Oracle is the best for warehousing standardized data, but not a good choice when considering unstructured data, or a mix of the two.
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.
Does not require continous attention from the DBA, autonomous features allows the database to perform most of the regular admin tasks without need for human intervention.
Allows to integrate multiple data sources on a central data warehouse, and explode the information stored with different analytic and reporting tools.
Hive is a very good big data analysis and ad-hoc query platform, which supports scaling also. The BI processes can be easily integrated with Hadoop via the Hive. It can deal with a much larger data set that traditional RDBMS can not. It is a "must-have" component of the big data domain.
Apache Hive is a FOSS project and its open source. We need not definitely comment on anything about the support of open source and its developer community. But, it has got tremendous developer support, awesome documentation. I would justify the fact that much support can be gathered from the community backup.
Understanding Oracle Cloud Infrastructure is really simple, and Autonomous databases are even more. Using shared or dedicated infrastructure is one of the few things you need to consider at the moment of starting provisioning your Oracle Autonomous Data Warehouse.
Besides Hive, I have used Google BigQuery, which is costly but have very high computation speed. Amazon Redshift is the another product, I used in my recent organisation. Both Redshift and BigQuery are managed solution whereas Hive needs to be managed
Cloudera is compatible with Windows operating systems, and Mac allows cloud-based deployment, it is also very useful to configure data encryption, guarantee protocols, and security policies. It also provides integrated auditing and monitoring capabilities, as well as a control comprehensive data repository for the enterprise, and ensures vendor compatibility through its open-source architecture.
As I mentioned, I have also worked with Amazon Redshift, but it is not as versatile as Oracle Autonomous Data Warehouse and does not provide a large variety of products. Oracle Autonomous Data Warehouse is also more reliable than Amazon Redshift, hence why I have chosen it
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.
Overall the business objective of all of our clients have been met positively with Oracle Data Warehouse. All of the required analysis the users were able to successfully carry out using the warehouse data.
Using a 3-tier architecture with the Oracle Data Warehouse at the back end the mid-tier has been integrated well. This is big plus in providing the necessary tools for end users of the data warehouse to carry out their analysis.
All of the various BI products (OBIEE, Cognos, etc.) are able to use and exploit the various analytic built-in functionalities of the Oracle Data Warehouse.
