Apache HBase vs MongoDB Enterprise Advanced comparison

Apache and MongoDB are both solutions in the NoSQL Databases category. Apache is ranked #9 with an average rating of 8.3, while MongoDB is ranked #1 with an average rating of 8.4. Apache holds a 5.6% mindshare in ND, compared to MongoDB’s 13.9% mindshare. Additionally, 75% of Apache users are willing to recommend the solution, compared to 92% of MongoDB users who would recommend it.

Apache HBase

Read 4 Apache HBase reviews

1,051 Views
998 Comparison Views

75% willing to recommend

MongoDB Enterprise Advanced

Read 82 MongoDB Enterprise Advanced reviews

5,473 Views
3,065 Comparison Views

92% willing to recommend

Apache HBase

MongoDB Enterprise Advanced

Comparison Buyer's Guide

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Executive SummaryUpdated on Nov 2, 2025

MongoDB Enterprise Advanced and Apache HBase compete in the database application category. MongoDB Enterprise Advanced might have the upper hand due to its robust support and usability features, while Apache HBase provides notable scalability and performance for big data operations.

Features: MongoDB Enterprise Advanced offers comprehensive security, automation, and integration with modern development environments, ensuring a seamless experience for businesses. Apache HBase is favored for handling large-scale data transactions, ensuring high availability and efficient failover support, making it suitable for organizations managing extensive data flows.

Room for Improvement: MongoDB Enterprise Advanced could enhance its handling of high-density writes and scaling under extreme conditions. Additionally, simplifying complex query optimization could benefit many users. Apache HBase might improve by streamlining deployment complexity, enhancing user documentation, and introducing more intuitive interface options for non-expert users.

Ease of Deployment and Customer Service: MongoDB Enterprise Advanced simplifies deployment with extensive customer service support, ideal for enterprises seeking smooth implementation. Apache HBase, although complex to deploy, provides powerful results and offers technical support options for detailed and intricate requirements, benefiting those who manage its deployment challenges.

Pricing and ROI: MongoDB Enterprise Advanced presents a higher setup cost but offers a robust ROI through its feature-rich platform, attracting organizations focusing on immediate and long-term benefits. Apache HBase, while more cost-effective upfront, provides a solid ROI with its high-performance capabilities and scalability, appealing to companies prioritizing efficient large data processing.

To learn more, read our detailed Apache HBase vs. MongoDB Enterprise Advanced Report (Updated: December 2025).

Buyer's Guide

Apache HBase vs. MongoDB Enterprise Advanced

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

9th

Average Rating

7.2

Reviews Sentiment

5.1

Number of Reviews

Ranking in other categories

No ranking in other categories

MongoDB Enterprise Advanced

Ranking in NoSQL Databases

1st

Average Rating

8.2

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Open Source Databases (6th), Managed NoSQL Databases (4th)

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 MongoDB Enterprise Advanced is 13.9%, down from 20.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

NoSQL Databases Market Share Distribution
Product	Market Share (%)
MongoDB Enterprise Advanced	13.9%
Apache HBase	5.6%
Other	80.5%

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.

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Fabien GOUINEAU

Architecte Cloud at Visiativ SA

Offers reliable engine for legacy needs but requires enhanced cost management and AI features

While MongoDB is a good product, it is also an expensive product for support, and its scalability is acceptable, but the big problem with MongoDB is the cost. For security in MongoDB, we work with encrypted databases by default, but we have not contracted the security options in our contract because it is too expensive, so we only implement encrypted databases without the security pack, which is very expensive for us; in security, we are at the first steps, just using encrypted databases. I think additional features needed in MongoDB include perhaps vector databases, as I think they are not supported right now.

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."

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

"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."

"MongoDB is extremely developer-friendly because when you are starting, there is very little time needed upfront in terms of planning."

"We find the query and speed very valuable."

"The most valuable features of MongoDB are the variety of translations available and the ability to deploy it on the cloud is useful. The cloud users can access the data, work on the data, and if they want to import or manipulate some data they can."

"It's super easy to develop a couple of solutions for clients with MongoDB, like a quick web page with no clear data structure that they need to spin up quickly to validate some sort of MDTP."

"My impression is that the initial setup is straightforward."

"MongoDB is fast and efficient."

"Its flexibility, and cost. It is reasonably priced."

"MongoDB is flexible and it allows other applications to be added."

More MongoDB Enterprise Advanced 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."

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

"We've seen 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."

"Enhancing the documentation to make it more beginner-friendly is crucial."

"From my point of view, they need a totally free IDE to work at high levels."

"The scalability of the solution has room for improvement."

"There is room for improvement in integrating MongoDB with agentive AI solutions."

"Sometimes, the tool goes down temporarily. There are some stability issues in the product."

"The solution could have more integration."

"The stability could be better."

"The performance could be faster."

More MongoDB Enterprise Advanced cons

Pricing and Cost Advice

Information not available

"MongoDB is a bit expensive compared to its competitors."

"I chose MongoDB because it is cost-effective compared to Oracle, which can be expensive. In addition, MongoDB has good performance and has not caused any issues while working with it. It has been a good choice for me."

"There is an enterprise license and it could be cheaper. We are using the free open source version."

"The product is affordable."

"I'm using the free version of MongoDB."

"I don't know, but I have heard from people who procure it that it is much cheaper than Oracle."

"MongoDB is a free solution. We wanted to have high availability and the subscription cost was quite expensive because the basic one is free and then when you want to have some other replications or other features you will need to pay money. Overall the solution is expensive."

"MongoDB's pricing is not reasonable, but it is not as expensive as the others."

More MongoDB Enterprise Advanced pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Manufacturing Company

10%

University

Comms Service Provider

Financial Services Firm

14%

Computer Software Company

Manufacturing Company

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	35
Midsize Enterprise	13
Large Enterprise	38

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 MongoDB?

MongoDB's approach to handling data in documents rather than traditional tables has been particularly beneficial.

See all answers

What is your experience regarding pricing and costs for MongoDB?

For a small company, the cost of MongoDB Enterprise Advanced is reasonable, but for heavy data usage, we see a little bit of cost pressure but it's acceptable. I will not be able to elaborate on th...

See all answers

What needs improvement with MongoDB?

The integration between data warehouse could be improved. Nowadays, a lot of data is getting generated, so certain ETL flexible scripts with backend database integrations would be an improvement I ...

See all answers

Comparisons

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

Redis vs Apache HBase

Compared 8% of the time

InfluxDB vs Apache HBase

Compared 6% of the time

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InfluxDB vs MongoDB Enterprise Advanced

Compared 6% of the time

Microsoft Azure Cosmos DB vs MongoDB Enterprise Advanced

Compared 5% of the time

Couchbase Enterprise vs MongoDB Enterprise Advanced

Compared 5% of the time

MongoDB Atlas vs MongoDB Enterprise Advanced

Compared 5% of the time

ScyllaDB vs MongoDB Enterprise Advanced

Compared 3% of the time

More MongoDB Enterprise Advanced Competitors

Product Reports

Buyer's Guide

NoSQL Databases

January 2026

Download Apache HBase product report

Buyer's Guide

MongoDB Enterprise Advanced

January 2026

Download MongoDB Enterprise Advanced 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

MongoDB Enterprise Advanced is a comprehensive platform renowned for its scalability, user-friendliness, and high performance, underpinned by its flexible document-based storage and open-source model. JSON compatibility, clustering, and security elevate its standing among professionals.

The platform facilitates efficient data management through developer-friendly tools and a strong aggregation framework. MongoDB’s no-schema requirement, supported by community expertise, underlines its adaptability. While its sharding capabilities and affordably support large data volumes, there are aspects such as security enhancement and enterprise tool integration that need attention. Indexing and query optimization pose challenges, alongside high costs. Improvements in analytics and UI could advance its infrastructure further.

What are the key features of MongoDB Enterprise Advanced?

Scalability: Dynamic adjustments to workloads with ease.
JSON Compatibility: Seamless data structuring with JSON support.
Clustering: Enhanced data management through robust clustering.
Security Integration: Built-in security measures for data protection.
Sharding: Efficient distribution of large datasets.

What benefits should users look for in reviews?

Document-Based Storage: Flexibility in managing varied data types.
Open-Source: Access to a broad community and resources.
Low-Cost Implementation: Economic efficiency in deployment.
Scalability: Supports the growth of data without sacrificing performance.

Industries leverage MongoDB Enterprise Advanced for significant roles in data storage within IoT platforms, healthcare apps, public service monitoring, and big data analytics. Companies in logistics and telecommunications find it instrumental for business process management and video content management, benefiting from its seamless integration and unstructured data support.

MongoDB

Sample Customers

Bloomberg, Wells Fargo, Apple, Capital One, NVIDIA

Facebook, MetLife, City of Chicago, Expedia, eBay, Google

Buyer's Guide

Apache HBase vs. MongoDB Enterprise Advanced

December 2025

Free Report: Apache HBase vs. MongoDB Enterprise Advanced

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