Denodo vs. Elasticsearch

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Denodo
Score 8.5 out of 10
N/A
Denodo is the eponymous data integration platform from the global company headquartered in Silicon Valley.N/A
Elasticsearch
Score 8.4 out of 10
N/A
Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.
$16
per month
Pricing
DenodoElasticsearch
Editions & Modules
No answers on this topic
Standard
$16.00
per month
Gold
$19.00
per month
Platinum
$22.00
per month
Enterprise
Contact Sales
Offerings
Pricing Offerings
DenodoElasticsearch
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
DenodoElasticsearch
Small Businesses

No answers on this topic

Algolia
Algolia
Score 8.9 out of 10
Medium-sized Companies
SAP HANA Cloud
SAP HANA Cloud
Score 8.5 out of 10
Guru
Guru
Score 9.0 out of 10
Enterprises
Delphix
Delphix
Score 9.2 out of 10
Guru
Guru
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
DenodoElasticsearch
Likelihood to Recommend
8.8
(6 ratings)
9.0
(47 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(1 ratings)
Usability
8.0
(1 ratings)
10.0
(1 ratings)
Performance
8.0
(1 ratings)
-
(0 ratings)
Support Rating
-
(0 ratings)
7.8
(9 ratings)
Implementation Rating
-
(0 ratings)
9.0
(1 ratings)
User Testimonials
DenodoElasticsearch
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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Elastic
Elasticsearch is a really scalable solution that can fit a lot of needs, but the bigger and/or those needs become, the more understanding & infrastructure you will need for your instance to be running correctly. Elasticsearch is not problem-free - you can get yourself in a lot of trouble if you are not following good practices and/or if are not managing the cluster correctly. Licensing is a big decision point here as Elasticsearch is a middleware component - be sure to read the licensing agreement of the version you want to try before you commit to it. Same goes for long-term support - be sure to keep yourself in the know for this aspect you may end up stuck with an unpatched version for years.
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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.
Read full review
Elastic
  • As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
  • Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
  • Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.
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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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Elastic
  • Joining data requires duplicate de-normalized documents that make parent child relationships. It is hard and requires a lot of synchronizations
  • Tracking errors in the data in the logs can be hard, and sometimes recurring errors blow up the error logs
  • Schema changes require complete reindexing of an index
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Likelihood to Renew
Denodo
No answers on this topic
Elastic
We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.
Read full review
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.
Read full review
Elastic
To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching. If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.
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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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Elastic
No answers on this topic
Support Rating
Denodo
No answers on this topic
Elastic
We've only used it as an opensource tooling. We did not purchase any additional support to roll out the elasticsearch software. When rolling out the application on our platform we've used the documentation which was available online. During our test phases we did not experience any bugs or issues so we did not rely on support at all.
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Implementation Rating
Denodo
No answers on this topic
Elastic
Do not mix data and master roles. Dedicate at least 3 nodes just for Master
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Alternatives Considered
Denodo
Denodo is simple and easy to use. Highly recommended unless you have huge volumes of data
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Elastic
As far as we are concerned, Elasticsearch is the gold standard and we have barely evaluated any alternatives. You could consider it an alternative to a relational or NoSQL database, so in cases where those suffice, you don't need Elasticsearch. But if you want powerful text-based search capabilities across large data sets, Elasticsearch is the way to go.
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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.
Read full review
Elastic
  • We have had great luck with implementing Elasticsearch for our search and analytics use cases.
  • While the operational burden is not minimal, operating a cluster of servers, using a custom query language, writing Elasticsearch-specific bulk insert code, the performance and the relative operational ease of Elasticsearch are unparalleled.
  • We've easily saved hundreds of thousands of dollars implementing Elasticsearch vs. RDBMS vs. other no-SQL solutions for our specific set of problems.
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