Apache HBase vs Microsoft Azure Cosmos DB comparison

Apache and Microsoft are both solutions in the NoSQL Databases category. Apache is ranked #10 with an average rating of 8.3, while Microsoft is ranked #2 with an average rating of 8.3. Apache holds a 5.1% mindshare in ND, compared to Microsoft’s 6.5% mindshare. Additionally, 75% of Apache users are willing to recommend the solution, compared to 95% of Microsoft users who would recommend it.

Apache HBase

Read 4 Apache HBase reviews

894 Views
858 Comparison Views

75% willing to recommend

Microsoft Azure Cosmos DB

Read 109 Microsoft Azure Cosmos DB reviews

9,566 Views
2,009 Comparison Views

95% willing to recommend

Apache HBase

Microsoft Azure Cosmos DB

Comparison Buyer's Guide

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Executive SummaryUpdated on Oct 19, 2025

Apache HBase and Microsoft Azure Cosmos DB are NoSQL database solutions, each offering unique benefits. Cosmos DB appears to have an advantage due to its advanced features like global distribution and multi-model support.

Features: HBase offers high scalability, strong consistency, and efficient large-scale data management. Its speed in read and write operations makes it suitable for distributed environments. Azure Cosmos DB provides global distribution, multiple data model support, and automatic indexing, enhancing its versatility and ease of use.

Room for Improvement: HBase needs improvements in user-friendliness and requires significant configuration efforts. Enhanced integration features and better documentation could address its complexity. For Cosmos DB, cost-effectiveness could be improved, along with offering more optimized solutions for specific use cases and expanding its support for complex queries.

Ease of Deployment and Customer Service: HBase deployment is challenging and requires ongoing maintenance, making it complex to implement. Cosmos DB, linked with the Azure ecosystem, enables quick deployment and benefits from Azure's customer service, which is comprehensive and supportive, simplifying database management.

Pricing and ROI: HBase typically involves lower setup costs due to its open-source nature but may vary in efficiency based on implementation. Cosmos DB, while having higher initial expenses, offers enhanced scalability and management efficiency, contributing to a strong ROI, making it appealing for performance-driven enterprises.

To learn more, read our detailed Apache HBase vs. Microsoft Azure Cosmos DB Report (Updated: December 2025).

Buyer's Guide

Apache HBase vs. Microsoft Azure Cosmos DB

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

Microsoft Azure Cosmos DB

Ranking in NoSQL Databases

2nd

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

109

Ranking in other categories

Database as a Service (DBaaS) (4th), Managed NoSQL Databases (1st), Vector Databases (1st)

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 Microsoft Azure Cosmos DB is 6.5%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

NoSQL Databases Market Share Distribution
Product	Market Share (%)
Microsoft Azure Cosmos DB	6.5%
Apache HBase	5.1%
Other	88.4%

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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reviewer2724105

Senior Director of Product Management at a tech vendor with 1,001-5,000 employees

Provides super sharp latency, excellent availability, and the ability to effectively manage costs across different tenants

For integrating Microsoft Azure Cosmos DB with other Azure products or other products, there are a couple of challenges with the current system. Right now, the vectors are stored as floating-point numbers within the NoSQL document, which makes them inefficiently large. This leads to increased storage space requirements, and searching through a vast number of documents in the vector database becomes quite costly in terms of RUs. While the integration works well, the expense associated with it is relatively high. I would really like to see a reduction in costs for their vector search, as it is currently on the expensive side. The areas for improvement in Microsoft Azure Cosmos DB are vector pricing and vector indexing patterns, which are unintuitive and not well described. I would also like to see the parameters of Fleet Spaces made more powerful, as currently, it's somewhat lightweight. I believe they've made those changes intentionally to better understand the cost model. However, we would like to take a more aggressive approach in using it. One of the most frustrating aspects of Microsoft Azure Cosmos DB right now is that you can only store one vector per document. Additionally, you must specify the configuration of that vector when you create an instance of Microsoft Azure Cosmos DB. Once the database is set up, you can't change the vector configuration, which is incredibly limiting for experimentation. You want the ability to try different settings and see how they perform, as there are numerous use cases for storing more than one vector in a document. While interoperability within the vector database is acceptable—for example, I can search for vectors—I still desire a richer set of configuration options.

Read full review

Quotes from Members

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

Pros

"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."

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

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

"The value that it has added to my AI or search workloads is that I think it's optimized that process and made it easier; we have a lot of unstructured data coming from different dissimilar systems and different data sources, so correlating those things together and making sense of it has been very beneficial."

"What I appreciate most are the latency and the access, which are guaranteed by the tool, which is really impressive."

"The most valuable features of Microsoft Azure Cosmos DB include the TTL, the ability to scale up and down as needed, and geo-replication, which comes out of the box."

"Microsoft Azure Cosmos DB is a Microsoft solution specifically, but we can develop with different developer kits for different databases."

"The solution is highly scalable."

"The solution is easy to use, and it is also easy to integrate with several things for database use cases."

"It performs very well, especially under high load where it automatically scales up the RUs, and the main advantage of Microsoft Azure Cosmos DB is its low latency, with response times in milliseconds, making it great for chatbots."

"The most valuable features for our organization with Azure Cosmos DB are multi-master capability for applications, automatic failover ensuring high availability, scalability, support for multiple data models, and low-latency access."

More Microsoft Azure Cosmos DB 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."

"We've seen performance issues."

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

"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."

"The challenge for us is always scale."

"In that scenario, two things can be improved."

"The size of the continuation token in Azure Cosmos DB should be static rather than increasing with more data, as it can lead to application crashes."

"The cost can sometimes be high, especially during cross-partition queries with large data amounts."

"It should offer a simple user interface for querying Microsoft Azure Cosmos DB."

"Continuing to educate customers on how they can take better advantage of Microsoft Azure Cosmos DB without having to completely rewrite their entire application paradigm would be beneficial."

"I do not have any specific suggestions for improvements at the moment. However, having more AI capabilities in the future would be beneficial."

"Azure Cosmos DB for NoSQL has a less developed interface and fewer SQL commands than MongoDB, and its community support is also smaller."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

Information not available

"The pricing is perceived as being on the higher side. However, if you have large data operations, it might reduce costs due to performance efficiencies."

"Cosmos DB is cost-effective when starting but requires careful management."

"Microsoft Azure Cosmos DB's licensing costs are monthly."

"Azure Cosmos DB is generally a costly resource compared to other Azure resources. It comes with a high cost. We have reserved one thousand RUs. Free usage is also limited."

"Cosmos DB is expensive compared to any virtual machine based on conventional RDBMS like MySQL or PostgreSQL."

"The cost is the biggest limitation of this solution."

"Everything could always be cheaper. I like that Cosmos DB allows us to auto-scale instead of pre-provisioning a certain capacity. It automatically scales to the demand, so we only pay for what we consume."

"For the cloud, we don't pay for the license, but for the on-prem versions, we do pay."

More Microsoft Azure Cosmos DB 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

Legal Firm

12%

Financial Services Firm

11%

Comms Service Provider

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	33
Midsize Enterprise	21
Large Enterprise	58

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...

See all answers

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 Microsoft Azure Cosmos DB?

The initial setup is simple and straightforward. You can set up a Cosmos DB in a day, even configuring things like availability zones around the world.

See all answers

What is your experience regarding pricing and costs for Microsoft Azure Cosmos DB?

Microsoft Azure Cosmos DB's pricing model has aligned with my budget expectations because I can tune the RU as I need to, which helps a lot. Microsoft Azure Cosmos DB's dynamic auto-scale or server...

See all answers

What needs improvement with Microsoft Azure Cosmos DB?

I have not utilized Microsoft Azure Cosmos DB multi-model support for handling diverse data types. I'm not in the position to decide if clients will use Microsoft Azure Cosmos DB or any other datab...

See all answers

Comparisons

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Compared 17% of the time

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Compared 16% of the time

ScyllaDB vs Apache HBase

Compared 15% of the time

Cassandra vs Apache HBase

Compared 8% of the time

SingleStore vs Apache HBase

Compared 4% of the time

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Chroma vs Microsoft Azure Cosmos DB

Compared 9% of the time

Pinecone vs Microsoft Azure Cosmos DB

Compared 8% of the time

Neo4j Graph Database vs Microsoft Azure Cosmos DB

Compared 7% of the time

MongoDB Enterprise Advanced vs Microsoft Azure Cosmos DB

Compared 6% of the time

Amazon DynamoDB vs Microsoft Azure Cosmos DB

Compared 5% of the time

More Microsoft Azure Cosmos DB Competitors

Product Reports

Buyer's Guide

NoSQL Databases

November 2025

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Buyer's Guide

Microsoft Azure Cosmos DB

December 2025

Download Microsoft Azure Cosmos DB product report

Also Known As

HBase

Microsoft Azure DocumentDB, MS Azure Cosmos DB

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

Microsoft Azure Cosmos DB offers scalable, geo-replicated, multi-model support with high performance and low latency. It provides seamless Microsoft service integration, benefiting those needing flexible NoSQL, real-time analytics, and automatic scaling for diverse data types and quick global access.

Azure Cosmos DB is designed to store, manage, and query large volumes of both unstructured and structured data. Its NoSQL capabilities and global distribution are leveraged by organizations to support activities like IoT data management, business intelligence, and backend databases for web and mobile applications. While its robust security measures and availability are strengths, there are areas for improvement such as query complexity, integration with services like Databricks and MongoDB, documentation clarity, and performance issues. Enhancements in real-time analytics, API compatibility, cross-container joins, and indexing capabilities are sought after. Cost management, optimization tools, and better support for local development also require attention, as do improvements in user interface and advanced AI integration.

What are the key features of Azure Cosmos DB?

Scalability: Effortlessly handles scaling for large workloads.
Geo-replication: Provides global data access with low latency.
Multi-model Support: Compatible with diverse data types.
NoSQL Flexibility: Offers a non-relational database experience.
Real-time Analytics: Facilitates data-driven decision-making.
Automation: Simplifies scaling and maintenance processes.

What benefits can users expect from Cosmos DB?

High Performance: Ensures rapid processing and low latency.
Ease of Use: Features a user-friendly interface enhancing deployment speed.
Seamless Integration: Connects effortlessly with Microsoft services.
Security: Offers robust measures to protect data integrity.
Consistent Availability: Ensures continuous access to data worldwide.

Industries use Azure Cosmos DB to support business intelligence and IoT data management, using its capabilities for backend databases in web and mobile applications. The platform's scalability and real-time analytics benefit sectors like finance, healthcare, and retail, where managing diverse datasets efficiently is critical.

Microsoft

Sample Customers

Bloomberg, Wells Fargo, Apple, Capital One, NVIDIA

TomTom, KPMG Australia, Bosch, ASOS, Mercedes Benz, NBA, Zero Friction, Nederlandse Spoorwegen, Kinectify

Buyer's Guide

Apache HBase vs. Microsoft Azure Cosmos DB

December 2025

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