Apache HBase vs Microsoft Azure Cosmos DB comparison

Apache and Microsoft are both solutions in the NoSQL Databases category. Apache is ranked #9 with an average rating of 8.3, while Microsoft is ranked #2 with an average rating of 8.3. Apache holds a 5.6% 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

1,051 Views
998 Comparison Views

75% willing to recommend

Microsoft Azure Cosmos DB

Read 109 Microsoft Azure Cosmos DB reviews

10,499 Views
2,205 Comparison Views

95% willing to recommend

Apache HBase

Microsoft Azure Cosmos DB

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Jan 25, 2026

Apache HBase and Microsoft Azure Cosmos DB compete in big data storage and management. While HBase is appreciated for its cost-effectiveness and compatibility, Cosmos DB gains an edge with advanced features and global scalability.

Features: Apache HBase supports large datasets and real-time processing with Hadoop compatibility. It handles high write and read speeds efficiently and benefits from in-memory processing. Microsoft Azure Cosmos DB offers multi-model database capabilities, strong consistency, and automatic global distribution, suitable for complex, scalable applications. It integrates seamlessly with other Microsoft products, supporting automatic failover and numerous data models.

Room for Improvement: Apache HBase could improve its ease of integration with non-Hadoop ecosystems, user-friendly interface, and real-time analytics. Cosmos DB might enhance its detailed documentation, cost management at scale, and data model flexibility. Solving schema-less design complexities and reducing latency for large-scale operations are areas that both platforms could address.

Ease Of Deployment and Customer Service: Apache HBase allows tailored deployments, but setup requires technical expertise. Although it integrates well with Hadoop infrastructures, significant technical know-how is necessary. Azure Cosmos DB simplifies deployment with managed cloud services and offers extensive support, aiding effortless scaling, seamless migration, and comprehensive customer service, ensuring smooth operations and support.

Pricing and ROI: Apache HBase has lower initial costs due to its open-source model, appealing to businesses with existing expertise. Azure Cosmos DB requires a higher initial outlay but provides a pay-as-you-go model that adapts to variable workloads. Its extensive features, including serverless capabilities, may lead to higher ROI for companies focusing on global distribution and minimal maintenance efforts.

To learn more, read our detailed Apache HBase vs. Microsoft Azure Cosmos DB Report (Updated: February 2026).

Buyer's Guide

Apache HBase vs. Microsoft Azure Cosmos DB

February 2026

Download the complete report

Helped 881,733 peers since 2012

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

9th

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 February 2026, in the NoSQL Databases category, the mindshare of Apache HBase is 5.6%, up from 4.8% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 6.5%, up from 2.0% 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	5.6%
Other	87.9%

NoSQL Databases

Featured Reviews

Ephrem Sisay

Senior Software Engineer at a computer software company with 501-1,000 employees

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.

Read full review

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 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 most valuable part is the column family structure."

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

"Latency and availability are incredible."

"It is integral to our business because it helps manage schema and metadata for all our documents and customers. The AI insights we glean based on Azure OpenAI also end up in Cosmos DB. We need a NoSQL store because the schema is dynamic and flexible, so Cosmos DB is a great fit. It has four nines or possibly five nines availability, excellent geo-distribution, and auto-scaling."

"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 feature of the solution is that it is scalable with multiple master files."

"Cosmos DB has helped our organization handle large amounts of data."

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

"The best feature is the velocity to make a query."

"The solution is used because we get faster response times with large data sets than with SQL."

More Microsoft Azure Cosmos DB pros

Cons

"We've seen performance issues."

"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."

"It's still new, and good training resources are harder to find. Even the most recent books on Cosmos DB are several years old, which is ancient in IT terms."

"The first one is the ability to assign role-based access control through the Azure portal for accounts to have contributor rights."

"An improvement would be a more robust functionality around updating elements on a document, or some type of procedural updates that don't require pulling the entire document."

"The integration with other solutions needs to improve because Cosmos DB's interoperability is lacking in some scenarios. For example, I'm currently implementing Fabric. That involves migrating from environments without apps, processing data and users, and taking them to Fabric."

"I would like to see Cosmos DB introduce a feature that would convert machine language to human-readable queries."

"An improvement could include increasing the document size or providing a method to manage larger sets efficiently. If they want to keep a 2 MB limit, they should provide a way to chain multiple documents in a systematic way so that developers do not have to figure out what to do when a document is larger than 2 MB."

"There is room for improvement in Microsoft's maintenance aspect. For example, we had a major incident at the end of December where the entire South Central region was down for our application, causing many problems due to a lack of access to the database."

"We'd like to avoid full DR replication if possible, as this would result in significant cost savings."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

Information not available

"There is a licensing fee."

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

"Right now, I have opted for the student subscription plan, for which Microsoft charges me around 100 USD. The pricing of the solution depends on the solution's usage."

"The solution is a bit on the expensive side."

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

"Microsoft provides fair pricing."

"Microsoft Azure Cosmos DB pricing is based on RUs. Reading 1 KB document costs one RU, whereas writing one document costs five RUs. Pricing for querying depends on the complexity of the query. If you increase the document size, it will automatically increase the RU cost."

"If you are a small organization or startup building from scratch without the Microsoft Startup Founder Club support, it could be expensive."

More Microsoft Azure Cosmos DB pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which NoSQL Databases solutions are best for your needs.

See recommendations

881,733 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

15%

Manufacturing Company

10%

University

Comms Service Provider

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

MongoDB Enterprise Advanced vs Apache HBase

Compared 15% of the time

Accumulo vs Apache HBase

Compared 13% of the time

ScyllaDB vs Apache HBase

Compared 13% of the time

Cassandra vs Apache HBase

Compared 8% of the time

Neo4j Graph Database vs Apache HBase

Compared 5% of the time

More Apache HBase Competitors

Pinecone vs Microsoft Azure Cosmos DB

Compared 7% of the time

Amazon DynamoDB vs Microsoft Azure Cosmos DB

Compared 7% of the time

Chroma vs Microsoft Azure Cosmos DB

Compared 6% of the time

Neo4j Graph Database vs Microsoft Azure Cosmos DB

Compared 6% of the time

MongoDB Enterprise Advanced vs Microsoft Azure Cosmos DB

Compared 6% of the time

More Microsoft Azure Cosmos DB Competitors

Product Reports

Buyer's Guide

NoSQL Databases

February 2026

Download Apache HBase product report

Buyer's Guide

Microsoft Azure Cosmos DB

January 2026

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

February 2026

Free Report: Apache HBase vs. Microsoft Azure Cosmos DB

Find out what your peers are saying about Apache HBase vs. Microsoft Azure Cosmos DB and other solutions. Updated: February 2026.

DOWNLOAD NOW

881,733 professionals have used our research since 2012.

See our Apache HBase vs. Microsoft Azure Cosmos DB report.

See our list of best NoSQL Databases vendors.

We monitor all NoSQL Databases reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.