Apache HBase vs MongoDB Enterprise Advanced comparison

Apache and MongoDB are both solutions in the NoSQL Databases category. Apache is ranked #10 with an average rating of 7.3, while MongoDB is ranked #1 with an average rating of 8.4. Apache holds a 5.2% mindshare in ND, compared to MongoDB’s 16.2% 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

865 Views
830 Comparison Views

75% willing to recommend

MongoDB Enterprise Advanced

Read 82 MongoDB Enterprise Advanced reviews

4,873 Views
3,021 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: September 2025).

Buyer's Guide

Apache HBase vs. MongoDB Enterprise Advanced

September 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

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 (4th), Managed NoSQL Databases (4th)

Mindshare comparison

As of November 2025, in the NoSQL Databases category, the mindshare of Apache HBase is 5.2%, up from 4.9% compared to the previous year. The mindshare of MongoDB Enterprise Advanced is 16.2%, down from 22.3% 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	16.2%
Apache HBase	5.2%
Other	78.6%

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.

Read full review

Uzair Faruqi

Head Of Analytics at Mjunction Services

Transforms data flow with adaptable schema and smooth public cloud deployment

One of our business units uses MongoDB, and we developed an ETL pipeline that extracts data from MongoDB and transfers it into our data warehouse MongoDB is a NoSQL database that is similar to a document database. It offers flexibility in schema adaptation, allowing us to change the schema and…

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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 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."

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

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

"One of the most valuable features of MongoDB is it is Its open source."

"It facilitates the generation of heatmaps for graphical data analysis."

"It is easy to set up."

"In our case, it is most important to have redundancy."

"We are using real-time analytics and monitoring in MongoDB Enterprise Advanced; it is integrated—the existing advanced feature is integrated with our business analytics interface, and all the various business intelligence reports are generated from that."

"It is convenient to use because we can do manipulations with the JSON data that we get. There are also a lot of joins and associations with MongoDB, which makes it easy to use for us."

"The Dynamic Application is a valuable feature."

"It is a stable solution. Stability-wise, I rate the solution a nine out of ten...Overall, MongoDB has helped manage and analyze attachment data."

More MongoDB Enterprise Advanced pros

Cons

"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."

"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."

"We've seen performance issues."

"The free tools, like MongoDB Compass, could be enhanced."

"The solution should more easily integrate with custom code."

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

"More stable indexes would be helpful in a future release. That's been an issue for some time. I don't know if it's been fixed now but we transitioned to it because we needed a search index to be able to search for things and if that goes or starts disappearing, we have to move away from that solution. I don't know if they fixed it, last time I had this issue was three years ago so they might have solved it."

"I think it would be good to have more search options such as an index resource. This will provide more options and resources to do advance searches."

"I'd like to see an ID generator. It's very technical but I don't think it has one, so we have to go to great lengths to work around that."

"The solution could have more integration."

"The solution should have better integration."

More MongoDB Enterprise Advanced cons

Pricing and Cost Advice

Information not available

"I currently use the solution's community edition which is free."

"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."

"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."

"I only used the open-source version."

"MongoDB has a free version. You can also buy the enterprise edition, which is cheaper than Oracle."

"It's open-source."

"This is an open-source solution."

"It is rather expensive."

More MongoDB Enterprise Advanced pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Comms Service Provider

Computer Software Company

University

Financial Services Firm

15%

Computer Software Company

11%

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 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?

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 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 17% of the time

ScyllaDB vs Apache HBase

Compared 13% of the time

Redis vs Apache HBase

Compared 7% of the time

Cassandra vs Apache HBase

Compared 7% of the time

Aerospike Database 7 vs Apache HBase

Compared 6% of the time

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InfluxDB vs MongoDB Enterprise Advanced

Compared 8% of the time

Couchbase Enterprise vs MongoDB Enterprise Advanced

Compared 7% of the time

Microsoft Azure Cosmos DB vs MongoDB Enterprise Advanced

Compared 6% of the time

Milvus vs MongoDB Enterprise Advanced

Compared 6% of the time

LanceDB vs MongoDB Enterprise Advanced

Compared 3% of the time

More MongoDB Enterprise Advanced Competitors

Product Reports

Buyer's Guide

NoSQL Databases

October 2025

Download Apache HBase product report

Buyer's Guide

MongoDB Enterprise Advanced

October 2025

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

September 2025

Free Report: Apache HBase vs. MongoDB Enterprise Advanced

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