What users are saying about
31 Ratings
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Score 8.2 out of 100
9 Ratings
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Score 8.3 out of 100

Likelihood to Recommend

Databricks Lakehouse Platform

Databricks has helped my teams write PySpark and Spark SQL jobs and test them out before formally integrating them in Spark jobs. Through Databricks we can create parquet and JSON output files. Datamodelers and scientists who are not very good with coding can get good insight into the data using the notebooks that can be developed by the engineers.
Anonymous | TrustRadius Reviewer

Denodo

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.
Anonymous | TrustRadius Reviewer

Pros

Databricks Lakehouse Platform

  • It supports all data science programming languages like Python and R
  • it takes very few minutes to deploy models into production
  • it has tools that ensures collaborations between developers
Kofi Joshua | TrustRadius Reviewer

Denodo

  • Flat learning curve.
  • Does not need brilliant developers.
  • Less need for custom denodo wrappers, even if needed is not very complex.
  • Denodo stored procedures and functions helped address complex, not straightforward requirements.
  • Export/import deployment between environments was very helpful.
Karthick Subharaj Rajarathinam | TrustRadius Reviewer

Cons

Databricks Lakehouse Platform

  • Better Localized Testing
  • When they were primarily OSS Spark; it was easier to test/manage releases versus the newer DB Runtime. Wish there was more configuration in Runtime less pick a version.
  • Graphing Support went non-existent; when it was one of their compelling general engine.
Anonymous | TrustRadius Reviewer

Denodo

  • 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?
Anonymous | TrustRadius Reviewer

Usability

Databricks Lakehouse Platform

Databricks Lakehouse Platform 9.0
Based on 1 answer
This has been very useful in my organization for shared notebooks, integrated data pipeline automation and data sources integrations. Integration with AWS is seamless. Non tech users can easily learn how to use Databricks. You can have your company LDAP connect to it for login based access controls to some extent
Anonymous | TrustRadius Reviewer

Denodo

Denodo 8.0
Based on 1 answer
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.
Anonymous | TrustRadius Reviewer

Performance

Databricks Lakehouse Platform

No score
No answers yet
No answers on this topic

Denodo

Denodo 8.0
Based on 2 answers
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.
Anonymous | TrustRadius Reviewer

Alternatives Considered

Databricks Lakehouse Platform

I also use Microsoft Azure Machine Learning in parallel with Databricks. They use different file formats which teach me to be flexible and able to write different programs. They are equally useful to me and I would like to master both platforms for any future usage. I do prefer Databricks because it could be free if I decided to go with the Databricks Community Edition only.
Ann Le | TrustRadius Reviewer

Denodo

I did not use any other data virtualization platform. BizTalk is not the right comparison; it is an integration layer and for orchestration; do not use denodo as an orchestration layer, it is not for connecting upstreams to downstreams and orchestrate data flows, it is primarily for pulling information and presenting in a fashion that benefit the audience
Karthick Subharaj Rajarathinam | TrustRadius Reviewer

Return on Investment

Databricks Lakehouse Platform

  • Rapid growth of analytics within our company.
  • Cost model aligns with usage allowing us to make a reasonable initial investment and scale the cost as we realize the value.
  • Platform is easy to learn and Databricks provides excellent support and training.
  • Platform does not require a large DevOPs investment
Anonymous | TrustRadius Reviewer

Denodo

  • Improved time-to-market. We addressed new requirements in less than 2 person days.
  • Very agile. Easy to handle changing requirements. Like a new requirement, a change in requirement was not expensive either.
  • Platform issues were difficult to diagnose and debug.
Karthick Subharaj Rajarathinam | TrustRadius Reviewer

Pricing Details

Databricks Lakehouse Platform

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Databricks Lakehouse Platform Editions & Modules

Edition
Standard$0.071
Premium$0.101
Enterprise$0.131
  1. Per DBU
Additional Pricing Details

Denodo

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Denodo Editions & Modules

Additional Pricing Details

Add comparison