Denodo vs. Oracle Data Service Integrator vs. SAP Data Intelligence

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.

Incentivized

Once Oracle Data Service Integrator is set up properly, it is quite simple to snatch data from a myriad of disparate sources and put them into a single repository. Due to cost factors, it is not for the faint of heart; however, if you can handle it, the benefits will quickly outpace the initial investment. To take full advantage of the power of ODSI, I would recommend the training that Oracle provides.

Incentivized

If you have an SAP products ecosystem in your IT landscape, it becomes a no-brainer to go ahead with an SAP Data Intelligence product for your data orchestration, data management, and advanced data analytics needs, such as data preparation for your AI/ML processes. It provides a seamless integration with other SAP products.

Incentivized

• Database Agnostic: You can easily connect to different environments and mash up data sets.
• The "magic" of data virtualization: No data is created, so data is reported in near-real-time to end users.
• It's easy to use UI for developers. You just connect to a data source, create tables, and join them to other datasets.

Incentivized

• Very easy to use. Very easy to just grab data when needed.
• Very robust and has so many features to move and transform data.
• Functionality is very easy to implement with other Oracle data products.

Incentivized

• It integrates well with our current ecosystem of SAP products, like HANA.
• It provides end-to-end machine learning operations, with tools for the complete model life cycle.
• It has a simple user interface for novice users, with complex tools also available for power users.
• It builds on SAP Data Hub, providing all the ETL functions of that tool with additional machine learning functionality.
• It can run in the cloud, no on-premise software management needed.
• Many programming languages are supported, it provides a sandbox environment for the user to develop in whichever style they prefer.
• SAP is very actively developing and improving it.

Incentivized

• 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.

Incentivized

• If not bundled with other products, the price can be prohibitively expensive
• SAP connectors tend to be a little expensive and slightly difficult to use
• The audit module had some difficulties debugging failed instances

Incentivized

• Data transfer speed tends to be slow when there is poor internet connection since SAP Data Intelligence don’t synchronize data while offline. However, this is not vendor fault, that’s why we have implemented robust wireless technology internet connection in our organization.

Incentivized

Allow collaborations among various personas
with insights as ratings and comments on the
datasets Reuse knowledges on the datasets for new users Next-Gen Data Management and Artificial Intelligence

Incentivized

Denodo is very easy to use. It has a user-friendly drag and drop interface. I'm not a fan of the java platform it resides on.

Incentivized

I think the troubleshooting process might be streamlined with improved error recording and tracing. A lot of information about issues and how to fix them is hidden away in the Kubernetes pods themselves. I'm not sure whether SAP Data Intelligence can fix this problem it may be connected to Kubernetes's design, in which case fixing it could need modifications inside Kubernetes itself.

Incentivized

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.

Incentivized

Initially we struggle to get help from SAP but then dedicated Dev angel was assigned to us and that simplify the overall support scenario. There is still room of improvement in documentation around SAP Data intelligence. We struggle a lot to initially understand the feature and required help around performance improvement area,

Incentivized

Denodo is simple and easy to use. Highly recommended unless you have huge volumes of data

Incentivized

While we tested and evaluated multiple data service providers, we came to choose Oracle Data Service Integrator since our infrastructure was so heavily dependent on Oracle software. The implementation would be easier and the difference in the number of features and performance wasn't enough to sway us in another direction.

Incentivized

One of the reasons to pick SAP Data Intelligence is the speed and security it provides, in addition to the excellent support it provides. It is also compatible with all popular databases, which is another reason to choose it.

Incentivized

• It is a huge advantage that we can connect to many different databases to provide data rapidly and accurately.
• It has proven to be a valuable environment for deploying data virtualization solutions, and its user community is active in finding and fixing issues.

Incentivized

• It provided terrific bulk data movement and data transformation services which we desperately needed
• It allowed to reduce development costs and lower the total cost of ownership among disparate architectures
• The enterprise edition's ELT allowed us to generate native code for wildly varied RDBMS

Incentivized

• Automation of data management slashed tasks by over 60% in most departments for the first 8 months.
• Metadata catalogs have enabled us to categorize data from disjointed sources in one place.
• It runs multiple ML models which enhances flexibility when managing data.

Incentivized