Denodo vs. Presto

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Denodo
Score 8.6 out of 10
N/A
Denodo is the eponymous data integration platform from the global company headquartered in Silicon Valley.N/A
Presto
Score 2.9 out of 10
N/A
Presto is an open source SQL query engine designed to run queries on data stored in Hadoop or in traditional databases. Teradata supported development of Presto followed the acquisition of Hadapt and Revelytix.N/A
Pricing
DenodoPresto
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
DenodoPresto
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Best Alternatives
DenodoPresto
Small Businesses

No answers on this topic

SingleStore
SingleStore
Score 9.7 out of 10
Medium-sized Companies
SAP HANA Cloud
SAP HANA Cloud
Score 8.5 out of 10
SingleStore
SingleStore
Score 9.7 out of 10
Enterprises
Delphix
Delphix
Score 9.1 out of 10
SingleStore
SingleStore
Score 9.7 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
DenodoPresto
Likelihood to Recommend
8.8
(6 ratings)
7.8
(2 ratings)
Usability
8.0
(1 ratings)
-
(0 ratings)
Performance
8.0
(1 ratings)
-
(0 ratings)
User Testimonials
DenodoPresto
Likelihood to Recommend
Denodo
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.
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Open Source
Presto is for interactive simple queries, where Hive is for reliable processing. If you have a fact-dim join, presto is great..however for fact-fact joins presto is not the solution.. Presto is a great replacement for proprietary technology like Vertica
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Pros
Denodo
  • 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.
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Open Source
  • Linking, embedding links and adding images is easy enough.
  • Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope).
  • Organizing & design is fairly simple with click & drag parameters.
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Cons
Denodo
  • 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.
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Open Source
  • Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem.
  • Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override.
  • UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.
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Usability
Denodo
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.
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Open Source
No answers on this topic
Performance
Denodo
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.
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Open Source
No answers on this topic
Alternatives Considered
Denodo
Denodo is simple and easy to use. Highly recommended unless you have huge volumes of data
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Open Source
Presto is good for a templated design appeal. You cannot be too creative via this interface - but, the layout and options make the finalized visual product appealing to customers. The other design products I use are for different purposes and not really comparable to Presto.
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Return on Investment
Denodo
  • 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.
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Open Source
  • Presto has helped scale Uber's interactive data needs. We have migrated a lot out of proprietary tech like Vertica.
  • Presto has helped build data driven applications on its stack than maintain a separate online/offline stack.
  • Presto has helped us build data exploration tools by leveraging it's power of interactive and is immensely valuable for data scientists.
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ScreenShots