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Great enterprise data virtualization tool with a few setbacks
June 08, 2019

Great enterprise data virtualization tool with a few setbacks

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with Denodo

We have implemented Denodo to several client sites. Most of the clients approached us to help them get out of their outdated systems, and we have recommended Denodo a few times since the tool virtualizes datasets which can be advantageous over persisting information into siloed databases.
  • 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.
  • Lack of Documentation and user community: Denodo continues to have a small community of super users, therefore there is not a lot of documentation out there in the event you get stuck.
  • Cost: Data virtualization isn't cheap, so smaller organizations might shy away from this technology due to the high licensing costs.
  • Caching strategy: Some slower datasets will require caching... which argues, why not just do traditional ETL if you need to do this?
  • Positive ROI for one client who was paying too much for an existing legacy reporting platform that hasn't been updated in decades.
  • Positive ROI for another client that didn't have any traditional BI tools.
  • A positive experience for end users who can now run a report using multiple data sources in near real time.
We evaluated other data virtualization platforms such as Cisco Composite. We found that Composite had an even smaller community and less support than Denodo. Denodo is putting a lot of the revenue earned from licensing costs to grow the product, and we did not get that vibe from Composite.
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.
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.
Donodo is very well suited for large organizations with siloed datasets. Denodo thrives in these environments, since large organizations can afford the licensing costs, and are always tasked to mash up data from multiple environments throughout the organization.