Apache HBase vs Cloudera Distribution for Hadoop comparison

Apache and Cloudera are both solutions in the NoSQL Databases category. Apache is ranked #10 with an average rating of 8.3, while Cloudera is ranked #8 with an average rating of 8.3. Apache holds a 5.1% mindshare in ND, compared to Cloudera’s 3.2% mindshare. Additionally, 75% of Apache users are willing to recommend the solution, compared to 92% of Cloudera users who would recommend it.

Apache HBase

Read 4 Apache HBase reviews

894 Views
858 Comparison Views

75% willing to recommend

Cloudera Distribution for H...

Read 51 Cloudera Distribution for Hadoop reviews

1,891 Views
529 Comparison Views

92% willing to recommend

Apache HBase

Cloudera Distribution for H...

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Executive SummaryUpdated on Jan 7, 2025

Cloudera Distribution for Hadoop and Apache HBase compete in the big data landscape, offering complementary data management and NoSQL database solutions. While Cloudera has superior integration capabilities, HBase stands out in high-speed data access and query performance, especially for real-time analytics.

Features: Cloudera Distribution for Hadoop is known for robust data processing, extensive ecosystem support, and ability to enable diverse analytics applications. Apache HBase offers scalability, efficient handling of large datasets, and real-time read/write access, ideal for transactional data processing.

Ease of Deployment and Customer Service: Cloudera provides streamlined deployment through robust tools and professional support, reducing complexities in large-scale implementations. HBase offers simpler deployment but may require additional technical expertise for optimization. Cloudera's customer service is comprehensive, whereas HBase relies on community-based support.

Pricing and ROI: Cloudera Distribution for Hadoop has higher initial setup costs but offers a promising ROI with integrated tools and enterprise-level features, leading to reduced infrastructure costs and enhanced efficiency. Apache HBase, being open-source, offers lower cost barriers, enabling budget savings, though organizations may need to invest in additional resources for support and management.

To learn more, read our detailed Apache HBase vs. Cloudera Distribution for Hadoop Report (Updated: December 2025).

Buyer's Guide

Apache HBase vs. Cloudera Distribution for Hadoop

December 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Apache HBase

Ranking in NoSQL Databases

10th

Average Rating

7.2

Reviews Sentiment

5.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Cloudera Distribution for H...

Ranking in NoSQL Databases

8th

Average Rating

8.0

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Hadoop (2nd)

Mindshare comparison

As of December 2025, in the NoSQL Databases category, the mindshare of Apache HBase is 5.1%, up from 4.8% compared to the previous year. The mindshare of Cloudera Distribution for Hadoop is 3.2%, up from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

NoSQL Databases Market Share Distribution
Product	Market Share (%)
Cloudera Distribution for Hadoop	3.2%
Apache HBase	5.1%
Other	91.7%

NoSQL Databases

Featured Reviews

Ephrem Sisay

DevOps Engineer (M-PESA) at Safaricom Ethiopia plc

In-memory processing and integration capabilities have optimized query performance

Apache HBase could be improved by optimizing the integration with Apache Phoenix; sometimes the abstraction and lookup jobs lead to issues when there are too many requests. Resource optimization isn't always as successful as it should be, which can cause some query and lookup jobs to fail. For instance, during eligibility checks for credit, if there are many requests on the database, it might fail, and after such a failure, it doesn't allow us to run queries from the moment they stop. If there could be optimization to require less resource usage and allow those jobs and queries to pick up from where they stopped, that would be a great addition to the tool.

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Rok Dolinsek

Manager, Bussines Development & Co Owner at Troia d.o.o.

Enables on-premise implementation with powerful data processing capabilities

This is the only solution that is possible to install on-premise. Cloudera provides a hybrid solution that combines compute on cloud or on-premises. It includes all machine learning algorithms in the Spark machine learning library. All functionalities needed for a big data platform and ETL are on the platform, eliminating the need for other tools. It is scalable, ready for vertical scaling, and very powerful, offering numerous functionalities and configurations for generative AI.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Apache HBase is a database used for data storage."

"The most valuable part is the column family structure."

"The in-memory processing lets us optimize our queries and helps us run concurrent queries and other jobs such as the lookup jobs we always use Apache HBase for."

"The best features of Apache HBase include being embedded, making it very fast; when it's linking, it operates with virtually no delay, and all of the queries are very fast too due to some internal optimization which makes it very sufficient and efficient."

"We experienced many issues when we started working with Hadoop 3.0 in the Cloudera 6.0 version, so there are a lot of things that need to improve. I believe they are working on that."

"It is helpful to gather and process data."

"We're now able to store large volumes of data through Cloudera Distribution for Hadoop. We're able to push large volumes of data to the platform, and that used to be a challenge, especially when storing a terabyte of information. This is the area where Cloudera Distribution for Hadoop improved the organization."

"Cloudera Distribution for Hadoop provides numerous features and capabilities combined into one platform, offers power processing, supports different file systems and query engines, and provides parallel processing for handling many requests."

"The most valuable feature is Kubernetes."

"The product as a whole is good."

"Cloudera, as a whole, is designed to provide organizations with solutions for big data."

"Customer service and support were able to fix whatever the issue was."

More Cloudera Distribution for Hadoop pros

Cons

"Apache HBase could be improved by optimizing the integration with Apache Phoenix; sometimes the abstraction and lookup jobs lead to issues when there are too many requests."

"The setup of Apache HBase needs a lot of time, and the linkage is not the program itself, but the activation and connecting to the NYPD engine always takes considerable time."

"We've seen performance issues."

"Apache HBase could be improved by optimizing the integration with Apache Phoenix; sometimes the abstraction and lookup jobs lead to issues when there are too many requests."

"I don't like using Apache HBase to store huge amounts of data because of many performance issues."

"The tool doesn't support reporting, and relational databases are still the major source of reporting data. Apache Iceberg will be launched soon within the Cloudera cluster for analytical purposes. The Cloudera Machine Learning aspect could be tuned and enhanced to enable us to host some predictive analytics machine learning and AI use cases."

"The Cloudera training has deteriorated significantly."

"The initial setup of Cloudera is difficult."

"They should focus on upgrading their technical capabilities in the market."

"The areas of improvement depend on the scale of the project. For banking customers, security features and an essential budget for commercial licenses would be the top priority. Data regulation could be the most crucial for a project with extensive data or an extra use case."

"We experienced many issues when we started working with Hadoop 3.0 in the Cloudera 6.0 version, so there is a lot of things that need to improve."

"There are better solutions out there that have more features than this one."

"This is a very expensive solution."

More Cloudera Distribution for Hadoop cons

Pricing and Cost Advice

Information not available

"The solution is fairly expensive."

"Cloudera requires a license to use."

"The price is very high. The solution is expensive."

"The product’s price depends from project to project."

"The solution is expensive."

"The tool is expensive...For the SMB market or customers whose environments are not that complex and do not have multiple systems running, Cloudera might not be a good option."

"It is an expensive product."

"I believe we pay for a three-year license."

More Cloudera Distribution for Hadoop pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Manufacturing Company

10%

Comms Service Provider

Computer Software Company

Educational Organization

18%

Financial Services Firm

18%

Computer Software Company

Energy/Utilities Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	16
Midsize Enterprise	9
Large Enterprise	31

Questions from the Community

What needs improvement with Apache HBase?

See all answers

What advice do you have for others considering Apache HBase?

I'm working for a corporate that uses Apache HBase for their Big Data platform and I'm a Big Data engineer there. We're using a version of Apache HBase that is compatible with the other Big Data to...

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What is your experience regarding pricing and costs for Apache HBase?

The cost depends on the EC2 instances and the size of the data you're indexing.

See all answers

What do you like most about Cloudera Distribution for Hadoop?

The tool can be deployed using different container technologies, which makes it very scalable.

See all answers

What is your experience regarding pricing and costs for Cloudera Distribution for Hadoop?

The price for Cloudera is average, yet it is very good compared to other solutions. It can be deployed on-premises, unlike competitors' cloud-only solutions.

See all answers

What needs improvement with Cloudera Distribution for Hadoop?

If they could support modifying the data more easily than the current implementation, it would be beneficial.

See all answers

Comparisons

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Compared 16% of the time

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Compared 15% of the time

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Compared 8% of the time

Microsoft Azure Cosmos DB vs Apache HBase

Compared 4% of the time

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Compared 18% of the time

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Compared 14% of the time

MongoDB Enterprise Advanced vs Cloudera Distribution for Hadoop

Compared 12% of the time

Couchbase Enterprise vs Cloudera Distribution for Hadoop

Compared 10% of the time

Cloudera Data Platform vs Cloudera Distribution for Hadoop

Compared 4% of the time

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Product Reports

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NoSQL Databases

November 2025

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Buyer's Guide

Cloudera Distribution for Hadoop

December 2025

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Also Known As

HBase

No data available

Overview

Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's BigTable. Just as Bigtable leverages the distributed data storage provided by the Google File System, Apache HBase provides Bigtable-like capabilities on top of Hadoop and HDFS.

Apache

Cloudera Distribution for Hadoop is the world's most complete, tested, and popular distribution of Apache Hadoop and related projects. CDH is 100% Apache-licensed open source and is the only Hadoop solution to offer unified batch processing, interactive SQL, and interactive search, and role-based access controls. More enterprises have downloaded CDH than all other such distributions combined.

Cloudera

Sample Customers

Bloomberg, Wells Fargo, Apple, Capital One, NVIDIA

37signals, Adconion,adgooroo, Aggregate Knowledge, AMD, Apollo Group, Blackberry, Box, BT, CSC

Buyer's Guide

Apache HBase vs. Cloudera Distribution for Hadoop

December 2025

Free Report: Apache HBase vs. Cloudera Distribution for Hadoop

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