Denodo is the eponymous data integration platform from the global company headquartered in Silicon Valley.
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Oracle Warehouse Builder
Score 8.7 out of 10
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Oracle Warehouse Builder (OWB) is a data-warehousing centered data integration solution, from Oracle. It offers basic ETL functionality for building a simple data warehouse, as well as advanced ETL functionality supporting enterprise data integration projects, along with connectivity for Oracle and SAP applications.
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Pricing
Denodo
Oracle Warehouse Builder
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Denodo
Oracle Warehouse Builder
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Denodo
Oracle Warehouse Builder
Features
Denodo
Oracle Warehouse Builder
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Denodo
-
Ratings
Oracle Warehouse Builder
9.5
5 Ratings
14% above category average
Connect to traditional data sources
00 Ratings
10.05 Ratings
Connecto to Big Data and NoSQL
00 Ratings
9.02 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Denodo
-
Ratings
Oracle Warehouse Builder
10.0
5 Ratings
20% above category average
Simple transformations
00 Ratings
10.05 Ratings
Complex transformations
00 Ratings
10.04 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Denodo
-
Ratings
Oracle Warehouse Builder
8.2
5 Ratings
4% above category average
Data model creation
00 Ratings
10.04 Ratings
Metadata management
00 Ratings
6.04 Ratings
Business rules and workflow
00 Ratings
9.04 Ratings
Collaboration
00 Ratings
8.94 Ratings
Testing and debugging
00 Ratings
7.04 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Denodo allows us to create and combine new views to create a virtual repository and APIs without a single line of code. It is excellent because it can present connectors with a view format for downstream consumers by flattening a JSON file. Reading or connecting to various sources and displaying a tabular view is an excellent feature. The product's technical data catalog is well-organized.
The best place for Oracle Warehouse Builder is at the business IT level. It's not suited for business-level users. They are easy confused. One way to reduce the confusion for the developers is to set up the workspaces based on the requirements that are discovered in design sessions. Once this is complete, the implementation of Oracle Warehouse Builder can take flight and be successful.
Caching - but I am sure it will be improved by now. There were times when we expected the cache to be refreshed but it was stale.
Schema generation of endpoints from API response was sometimes incomplete as not all API calls returned all the fields. Will be good to have an ability to load the schema itself (XSD/JSON/Soap XML etc).
Denodo exposed web services were in preliminary stage when we used; I'm sure it will be improved by now.
Export/Import deployment, while it was helpful, there were unexpected issues without any errors during deployment. Issues were only identified during testing. Some views were not created properly and did not work. If it was working in the environment from where it was exported from, it should work in the environment where it is imported.
What I noticed is that sometimes OWB doesn't generate the best SQL in the package especially when there are a high number of source tables in the ETL. It would be nice if ETL developers were allowed to update the generated packages in the database directly.
Another thing - moving OWB ETLs from one database to another one could be easier - for example it would be nice to just copy the generated packages from one database to the other one without doing the deployment of these ETLs through OWB.
Denodo is a tool to rapidly mash data sources together and create meaningful datasets. It does have its downfalls though. When you create larger, more complex datasets, you will most likely need to cache your datasets, regardless of how proper your joins are set up. Since DV takes data from multiple environments, you are taxing the corporate network, so you need to be conscious of how much data you are sending through the network and truly understand how and when to join datasets due to this.