Denodo is the eponymous data integration platform from the global company headquartered in Silicon Valley.
N/A
Tableau Desktop
Score 8.3 out of 10
N/A
Tableau Desktop is a data visualization product from Tableau. It connects to a variety of data sources for combining disparate data sources without coding. It provides tools for discovering patterns and insights, data calculations, forecasts, and statistical summaries and visual storytelling.
$75
per month
Pricing
Denodo
Tableau Desktop
Editions & Modules
No answers on this topic
Tableau
$75
per month per user
Tableau Enterprise
$115
per month per user
Offerings
Pricing Offerings
Denodo
Tableau Desktop
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
All pricing plans are billed annually.
More Pricing Information
Community Pulse
Denodo
Tableau Desktop
Features
Denodo
Tableau Desktop
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Denodo
-
Ratings
Tableau Desktop
8.4
174 Ratings
3% above category average
Pixel Perfect reports
00 Ratings
8.1144 Ratings
Customizable dashboards
00 Ratings
8.9173 Ratings
Report Formatting Templates
00 Ratings
8.1150 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Denodo
-
Ratings
Tableau Desktop
8.2
171 Ratings
2% above category average
Drill-down analysis
00 Ratings
8.3166 Ratings
Formatting capabilities
00 Ratings
8.3169 Ratings
Integration with R or other statistical packages
00 Ratings
7.8125 Ratings
Report sharing and collaboration
00 Ratings
8.4164 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Denodo
-
Ratings
Tableau Desktop
8.1
165 Ratings
2% below category average
Publish to Web
00 Ratings
7.9154 Ratings
Publish to PDF
00 Ratings
7.7153 Ratings
Report Versioning
00 Ratings
7.9119 Ratings
Report Delivery Scheduling
00 Ratings
8.7127 Ratings
Delivery to Remote Servers
00 Ratings
8.277 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization 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 scenario is definitely to collect data from several sources and create dedicated dashboards for specific recipients. However, I miss the possibility of explaining these reports in more detail. Sometimes, we order a report, and after half a year, we don't remember the meaning of some data (I know it's our fault as an organization, but the tool could force better practices).
An excellent tool for data visualization, it presents information in an appealing visual format—an exceptional platform for storing and analyzing data in any size organization.
Through interactive parameters, it enables real-time interaction with the user and is easy to learn and get support from the community.
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.
Our use of Tableau Desktop is still fairly low, and will continue over time. The only real concern is around cost of the licenses, and I have mentioned this to Tableau and fully expect the development of more sensible models for our industry. This will remove any impediment to expansion of our use.
Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.
When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.
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.
Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast
Tableau support has been extremely responsive and willing to help with all of our requests. They have assisted with creating advanced analysis and many different types of custom icons, data formatting, formulas, and actions embedded into graphs. Tableau offers a weekly presentation of features and assists with internal company projects.
It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.
I think the training was good overall, but it was maybe stating the obvious things that a tech savvy young engineer would be able to pick up themselves too. However, the example work books were good and Tableau web community has helped me with many problems
Again, training is the key and the company provides a lot of example videos that will help users discover use cases that will greatly assist their creation of original visualizations. As with any new software tool, productivity will decline for a period. In the case of Tableau, the decline period is short and the later gains are well worth it.
I have used Power BI as well, the pricing is better, and also training costs or certifications are not that high. Since there is python integration in Power BI where I can use data cleaning and visualizing libraries and also some machine learning models. I can import my python scripts and create a visualization on processed data.
Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.
Tableau was acquired years ago, and has provided good value with the content created.
Ongoing maintenance costs for the platform, both to maintain desktop and server licensing has made the continuing value questionable when compared to other offerings in the marketplace.
Users have largely been satisfied with the content, but not with the overall performance. This is due to a combination of factors including the performance of the Tableau engines as well as development deficiencies.