Apache Hive vs. Oracle Autonomous Data Warehouse vs. Oracle Hyperion (legacy)

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.

Incentivized

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.

Incentivized

Well suited: For use in multiple offices around the world. I was able to obtain financial reporting data from 5 foreign offices and then consolidate their data with 3 domestic USA offices to prepare a consolidated financial statement. Less Appropriate: Translating the financial value for consulting services could be a bit challenging because that required human interaction and judgement. It would have been great to be able to set up some software to be able to interpret this and let it run for all future project work revenue projection.

Incentivized

• 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.

Incentivized

• 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.

• This product handles budgeting by Employee and/or Position very well. It is highly flexible and allows Hyperion administrators the ability to develop a planning application that fits a variety of different business needs.
• It is great at calculating benefits using business rules to automate the population of these fringe costs in the overall budget planning process. This greatly reduces user error.
• It allows you to seed the operating budget based on changes to key drivers, such as percentage increases, flat dollar increases and more detailed changes using business rules.
• Allows visibility into the plans for each unit across the organization, rolled up into an overall budget for the campus.
• It handles the creation of budgets with multiple chartfield segments or dimensions, which most other budgeting systems cannot handle well. It can aggregate these very quickly.

Incentivized

• Some queries, particularly complex joins, are still quite slow and can take hours
• Previous jobs and queries are not stored sometimes
• Switching to Impala can sometimes be time-consuming (i.e. the system hangs, or is slow to respond).
• Sometimes, directories and tables don't load properly which causes confusion

Incentivized

• 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.

Incentivized

• One pain point for us is the consolidation and translation process. Needing to translate the data over and over again is frustrating and there is no visibility into how many users are running a translation. If multiple users attempt to translate the same data set, say goodbye to your performance but you have no way of knowing! (Unless you want to pull up a task audit which is not a very realistic expectation). It has the been the quickest way for us to bring the system to it's knees. The consolidation process performs in direct correlation to the complexity of the calculation/consolidation rules. So, while the product is extremely flexible, you still have to be careful how you design your rules and calculations to make sure that you do it on the smallest subset of data as possible to avoid large processing times. This makes sense, but requires some significant expertise that most organizations do not have in-house.
• The Hyperion Financial Reporting product is ridiculously outdated and clunky to use. The interface for designing reports is not intuitive, and not easy to modify once a report is built. I think there must be a strategic decision to move away from it and go to something more like Oracle BI because I just can't understand why in the world they don't update the reporting product. It also requires a significant level of expertise to be able to use. Not a great solution at all if you want multiple end-users to create reports in something other than Excel. Nobody except the HFM admin (which I used to be) in our company even touches this module.
• Another pain point is the amount of IT support that is required to run this thing, and again, specialized knowledge of Hyperion products and how they work is required for IT to adequately support it. This goes for application servers and the Oracle database that the applications are running on.

Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.

Because

• It is really simple to provision and configure.
• 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.

Incentivized

We're in the middle of the road because we are not sure that other products on the market fit the bill for what we need yet. Hyperion is expensive and burdensome from an administrator and maintenance standpoint, but it still seems to be the best solution for what we need. Show us an equally capable SaaS consolidation product and we'll talk again.

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.

Incentivized

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.

Incentivized

The premium support team provides much needed dedicated customer service which we are after for what we have paid for this service. We are satisfied with the service and support and do not have any instance where there was an issue that requires escalation to get the right support team. Though the incidence of major issues that requires the premium support are less, we prefer to keep this as a safety net.

Incentivized

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.

Incentivized

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

Incentivized

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

Incentivized

I use Oracle Hyperion Enterprise Performance Mangement because the company I work at requires me to use it in the Financial Planning sector as most of their data is stored in it. I am open minded and ready to use other performance management tools created by Oracle if my work permits.

Incentivized

• Apache hive is secured and scalable solution that helps in increasing the overall organization productivity.
• Apache hive can handle and process large amount of data in a sufficient time manner.
• It simplifies writing SQL queries, hence helping the organization as most companies use SQL for all query jobs.

Incentivized

• 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.

Incentivized

• Oracle Hyperion allows us to automate and consolidate financial data that used to be performed manually in spreadsheets. From that perspective the ROI is huge.
• Oracle Hyperion functionality is extensive and allows us to perform most functions for planning, consolidating and reporting on our financial data.
• One negative with Oracle Hyperion is that it is complicated to implement and maintain. It takes expertise at all levels (infrastructure and management) to realize the benefits from it.

Incentivized