Cloudera Enterprise Data Hub vs. Databricks Lakehouse Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Cloudera Enterprise Data Hub
Score 9.0 out of 10
N/A
The Cloudera Enterprise Data Hub powered by SDX is a multifunction analytics solution that supports a range of operational and analytic use cases for enterprises.N/A
Databricks Lakehouse Platform
Score 8.1 out of 10
N/A
Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data lakes, and data platforms. Users can manage full data journey, to ingest, process, store, and expose data throughout an organization. Its Data Science Workspace is a collaborative environment for practitioners to run…
$0.07
Per DBU
Pricing
Cloudera Enterprise Data HubDatabricks Lakehouse Platform
Editions & Modules
No answers on this topic
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
Offerings
Pricing Offerings
Cloudera Enterprise Data HubDatabricks Lakehouse Platform
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Cloudera Enterprise Data HubDatabricks Lakehouse Platform
Top Pros
Top Cons
Best Alternatives
Cloudera Enterprise Data HubDatabricks Lakehouse Platform
Small Businesses
Google BigQuery
Google BigQuery
Score 8.7 out of 10

No answers on this topic

Medium-sized Companies
Snowflake
Snowflake
Score 9.0 out of 10
Snowflake
Snowflake
Score 9.0 out of 10
Enterprises
Oracle Exadata
Oracle Exadata
Score 8.1 out of 10
Snowflake
Snowflake
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Cloudera Enterprise Data HubDatabricks Lakehouse Platform
Likelihood to Recommend
9.0
(12 ratings)
8.4
(17 ratings)
Likelihood to Renew
8.2
(7 ratings)
-
(0 ratings)
Usability
-
(0 ratings)
9.4
(3 ratings)
Support Rating
-
(0 ratings)
8.6
(2 ratings)
Contract Terms and Pricing Model
-
(0 ratings)
8.0
(1 ratings)
Professional Services
-
(0 ratings)
10.0
(1 ratings)
User Testimonials
Cloudera Enterprise Data HubDatabricks Lakehouse Platform
Likelihood to Recommend
Cloudera
Cloudera excels at seamless migrations and upgrades.



Cloudera supports self-healing and data center
replacement of failed cloud instances while maintaining the state.



Cloudera is essential to increase or decrease
capacity through the user interface or API.



Cloudera is great at simplifying big data analytics
by providing the technology and tools needed to gain insights from IoT and
connected devices to help monitor and condition our assets.



Cloudera's cybersecurity platform option offers
stronger anomaly detection, visibility, and prevention, as well as faster
behavioral analysis.



Cloudera is beneficial for enabling and utilizing
the platform's machine learning and ad-hoc queries while securely storing,
retrieving, and analyzing any volume of data at scale.
Read full review
Databricks
If you need a managed big data megastore, which has native integration with highly optimized Apache Spark Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.
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Pros
Cloudera
  • Excellent management capabilities via Cloudera Manager.
  • Open source and does not restrict our data to be bound by a proprietary format.
  • Offers excellent support for data governance and auditing.
  • Has all the components that would help us build a data hub.
  • Excellent platform support offered by Cloudera.
Read full review
Databricks
  • Process raw data in One Lake (S3) env to relational tables and views
  • Share notebooks with our business analysts so that they can use the queries and generate value out of the data
  • Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
  • Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers
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Cons
Cloudera
  • Not fully Open Source, couple of components of the distributions are privately owned, meaning with public contributions are not welcome
  • Improvements to Cloudera manager can only be recommended. its very hard to get it done once recommended as the full control is with them.
  • Should make components more aligned to Open Source rather than making it closed sourced.
  • Custom Features of open source software tools supported only by Cloudera are tricky. Cant commit changes to tools like Hue.
  • Improvements to Cluster Management tool is required, which are already available to its competitors.
Read full review
Databricks
  • Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
  • Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
  • Visualization in MLFLOW experiment can be enhanced
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Likelihood to Renew
Cloudera
Likely to renew the use in case the requirements for Cloudera remain valid. The rapid change in customer requirements and solutions that must be validated, integrated or tested changes. As the maturity of the solution increases, the requirements to renew use decrease. From a solution feature perspective by itself would probably grade 10.
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Databricks
No answers on this topic
Usability
Cloudera
No answers on this topic
Databricks
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

in terms of graph generation and interaction it could improve their UI and UX
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Support Rating
Cloudera
No answers on this topic
Databricks
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
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Alternatives Considered
Cloudera
Cloudera is
compatible with Windows operating systems, and Mac allows cloud-based
deployment, it is also very useful to configure data encryption, guarantee
protocols, and security policies. It also provides integrated auditing and
monitoring capabilities, as well as a control comprehensive data repository for
the enterprise, and ensures vendor compatibility through its open-source
architecture.
Read full review
Databricks
Compared to Synapse & Snowflake, Databricks provides a much better development experience, and deeper configuration capabilities. It works out-of-the-box but still allows you intricate customisation of the environment. I find Databricks very flexible and resilient at the same time while Synapse and Snowflake feel more limited in terms of configuration and connectivity to external tools.
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Return on Investment
Cloudera
  • Cloudera products are the most widely. It is more business friendly as data is more secure. The sensitive data that you operate on is local to you and your project rather than processing this data on Cloud.
  • Cloudera is definitely faster as wait time is reduced if on Cloud.
  • A lot range of products are covered. So it is definitely good for businesses and had good returns on investments.
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Databricks
  • The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
  • DB has the ability to terminate/time out instances which helps manage cost.
  • The ability to quickly access typical hard to build data scenarios easily is a strength.
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ScreenShots