Apache HBase vs Cassandra comparison

Apache HBase and Cassandra are both solutions in the NoSQL Databases category. Apache HBase is ranked #10 with an average rating of 7.3, while Cassandra is ranked #6 with an average rating of 8.2. Apache HBase holds a 5.4% mindshare in ND, compared to Cassandra’s 8.7% mindshare. Additionally, 75% of Apache HBase users are willing to recommend the solution, compared to 91% of Cassandra users who would recommend it.

Apache HBase

Read 4 Apache HBase reviews

869 Views
834 Comparison Views

75% willing to recommend

Cassandra

Read 24 Cassandra reviews

2,064 Views
1,507 Comparison Views

91% willing to recommend

Apache HBase

Cassandra

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Executive SummaryUpdated on Jan 7, 2025

Cassandra and Apache HBase are competing products in the distributed database category. Cassandra seems to have the upper hand due to its ease of use and scalability, while Apache HBase stands out for its strong consistency and integration capabilities.

Features: Cassandra offers high availability, fault tolerance, and support for multi-data center replication, making it ideal for applications prioritizing uptime. Apache HBase provides real-time read/write access to large datasets, tight integration with Hadoop ecosystems, and efficient column-oriented storage, which is suitable for analytics-heavy applications.

Ease of Deployment and Customer Service: Cassandra provides straightforward deployment with excellent community support. HBase involves a more complex deployment due to its dependence on the Hadoop ecosystem but offers robust training and documentation resources.

Pricing and ROI: Cassandra presents a lower setup cost with substantial ROI potential due to its open-source nature and cost-effective scaling options. Apache HBase, while also open-source, may involve higher indirect costs because of its Hadoop ecosystem dependency but offers value through comprehensive big data solutions.

To learn more, read our detailed Apache HBase vs. Cassandra Report (Updated: July 2025).

Buyer's Guide

Apache HBase vs. Cassandra

July 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

Cassandra

Ranking in NoSQL Databases

6th

Average Rating

8.0

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

Vector Databases (14th)

Mindshare comparison

As of September 2025, in the NoSQL Databases category, the mindshare of Apache HBase is 5.4%, up from 4.9% compared to the previous year. The mindshare of Cassandra is 8.7%, down from 13.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

NoSQL Databases Market Share Distribution
Product	Market Share (%)
Cassandra	8.7%
Apache HBase	5.4%
Other	85.9%

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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Himanshu Amodwala

Senior cloud solution architect at Microsoft

Well-equipped to handle a massive influx of data and billions of requests

The use of Cassandra in real-time data analytics has been pivotal for our e-commerce platform. As our platform operates 24/7, providing services to sellers and customers alike, the need for real-time updates is paramount. For instance, when a customer leaves comments or feedback on an image, they anticipate an immediate reflection of these changes on the portal. Similarly, sellers altering product attributes or updating images expect instant visibility of these modifications. Handling large data volumes with Cassandra has been an excellent experience. Despite challenges related to the influx, these were not attributed to Cassandra itself but rather to middle-layer issues. Generally, it demonstrated scalability with workloads, thanks to its horizontal scaling capabilities. We could easily add new nodes to the system as needed, ensuring the platform coped well with increasing loads. The tool's most beneficial feature for scalability is its entire architecture. The absence of a single point of failure or a leader within the ecosystem contributes to its robust scalability. This key aspect influenced our decision to opt for the Cassandra ecosystem. In terms of performance, it demonstrated the ability to handle approximately 1.6 billion requests per day. This was achieved on AWS using EC2 instances, and it was during a period about four to five years ago.

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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

"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."

"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."

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

"Cassandra has some features that are more useful for specific use cases where you have time series where you have huge amounts of writes. That should be quick, but not specifically the reads. We needed to have quicker reads and writes and this is why we are using Cassandra right now."

"Cassandra offers high availability and fault tolerance, making it suitable for large-scale data storage and real-time processing."

"Can achieve continuous data without a single downtime because of node to node ring architecture."

"I'd rate the solution ten out of ten."

"The most valuable features of this solution are its speed and distributed nature."

"The technical evaluation is very good."

"We can add almost one million columns to the solution."

"Our primary use case for the solution is testing."

More Cassandra pros

Cons

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

"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."

"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."

"We've seen performance issues."

"There were challenges with the query language and the development interface. The query language, in particular, could be improved for better optimization. These challenges were encountered while using the Java SDK."

"The disc space is lacking. You need to free it up as you are working."

"Interface is not user friendly."

"It can be difficult to analyze what's going on inside of the database relative to other databases. It can also be difficult to troubleshoot sometimes."

"There could be more integration, and it could be more user-friendly."

"Cassandra could be more user-friendly like MongoDB."

"Cassandra is very complex to manage. Sometimes, I need to involve a senior DevOps engineer if we encounter a problem."

"Fine-tuning was a bit of a challenge."

More Cassandra cons

Pricing and Cost Advice

Information not available

"Cassandra is a free open source solution, but there is a commercial version available called DataStax Enterprise."

"I use the tool's open-source version."

"We are using the open-source version of Cassandra, the solution is free."

"There are licensing fees that must be paid, but I'm not sure if they are paid monthly or yearly."

"We pay for a license."

"I don't have the specific numbers on pricing, but it was fairly priced."

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Top Industries

By visitors reading reviews

Financial Services Firm

20%

Computer Software Company

Comms Service Provider

University

Financial Services Firm

17%

Computer Software Company

13%

Retailer

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	1
Large Enterprise	13

Questions from the Community

What do you like most about Apache HBase?

Apache HBase is a database used for data storage.

See all answers

What needs improvement with Apache HBase?

We've seen performance issues when we have more regions. The product needs improvement in that area. So we experience performance issues sometimes when the load increases.

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What advice do you have for others considering Apache HBase?

It's better to use AWS DynamoDB or Cassandra. I would rate it an eight out of ten. It is easy for a beginner to learn.

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What do you like most about Cassandra?

See all answers

What is your experience regarding pricing and costs for Cassandra?

We are using Cassandra locally and as open-source.

See all answers

What needs improvement with Cassandra?

While Cassandra can handle NoSQL, I think there should be more flexibility for whole schema design when data is stored in wide columns. Additionally, I believe that eventual consistency should be e...

See all answers

Comparisons

Accumulo vs Apache HBase

Compared 21% of the time

MongoDB Enterprise Advanced vs Apache HBase

Compared 19% of the time

ScyllaDB vs Apache HBase

Compared 15% of the time

Redis vs Apache HBase

Compared 9% of the time

Couchbase Enterprise vs Apache HBase

Compared 5% of the time

More Apache HBase Competitors

MongoDB Enterprise Advanced vs Cassandra

Compared 15% of the time

ClickHouse vs Cassandra

Compared 13% of the time

Couchbase Enterprise vs Cassandra

Compared 11% of the time

ScyllaDB vs Cassandra

Compared 8% of the time

Milvus vs Cassandra

Compared 3% of the time

More Cassandra Competitors

Product Reports

Buyer's Guide

NoSQL Databases

August 2025

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Buyer's Guide

Cassandra

August 2025

Download Cassandra product report

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

Cassandra is a distributed and scalable database management system used for real-time data processing.

It is highly valued for its ability to handle large amounts of data, scalability, high availability, fault tolerance, and flexible data model.

It is commonly used in finance, e-commerce, and social media industries.

Apache

Sample Customers

Bloomberg, Wells Fargo, Apple, Capital One, NVIDIA

1. Apple 2. Netflix 3. Facebook 4. Instagram 5. Twitter 6. eBay 7. Spotify 8. Uber 9. Airbnb 10. Adobe 11. Cisco 12. IBM 13. Microsoft 14. Yahoo 15. Reddit 16. Pinterest 17. Salesforce 18. LinkedIn 19. Hulu 20. Airbnb 21. Walmart 22. Target 23. Sony 24. Intel 25. Cisco 26. HP 27. Oracle 28. SAP 29. GE 30. Siemens 31. Volkswagen 32. Toyota

Buyer's Guide

Apache HBase vs. Cassandra

July 2025

Free Report: Apache HBase vs. Cassandra

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