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.
Oracle Coherence can be used to solve latency problems by caching data near the application tier. In-memory performance helps to reduce data contention, thus improving application response time. Oracle Coherence does a great job at scaling linearly and can do so dynamically. Oracle Coherence can replicate data so it can be part of a disaster recovery solution. One thing that is often overlooked with elastic caches is their ability to analyze data in memory, leveraging the processing power of the data grid. This is something Oracle Coherence does exceptionally well. Oracle Coherence also provided event handling capabilities to allow applications to respond to events triggered by transactions.
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.
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.
Oracle Coherence support team is responsive and knowledgeable. We contacted them to ask a couple of design questions about how we were setting up Oracle Coherence based on how we used IBM's Datapower Extreme Scale. They were able to guide us so that we got the design correct the first time and didn't have to go back and re-architect our design later.
DataSynapse GridServer has the same cache functionality connected with a grid distributed application deployment platform. It provides all the necessary tools to configure and manage these applications. On the otherhand Oracle Coherence has more a flexible configuration and better performance. Also the Oracle configuration and monitoring tools are more convenient and informative than the DataSynapse ones.
In my current project, it is yet to be decided as we are on the way to make it live for users. But I am sure it will be an added value to obtain timely calculations.
