Apache HBase vs Google Cloud Firestore comparison

Apache and Google are both solutions in the NoSQL Databases category. Apache is ranked #10 with an average rating of 8.3, while Google is ranked #13 with an average rating of 8.3. Apache holds a 5.3% mindshare in ND, compared to Google’s 2.7% mindshare. Additionally, 75% of Apache users are willing to recommend the solution, compared to 100% of Google users who would recommend it.

Apache HBase

Read 4 Apache HBase reviews

958 Views
920 Comparison Views

75% willing to recommend

Google Cloud Firestore

Read 3 Google Cloud Firestore reviews

581 Views
331 Comparison Views

100% willing to recommend

Apache HBase

Google Cloud Firestore

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Executive SummaryUpdated on Jan 7, 2025

Apache HBase and Google Cloud Firestore both compete in the database solutions category. Firestore appears to have the upper hand due to its seamless integration with Google services and managed service advantages.

Features: Apache HBase is designed for large-scale non-relational data and excels in linear scalability and massive read/write throughput. It focuses on extensive data processing capabilities. Google Cloud Firestore offers real-time synchronization, automatic scaling, and integrates smoothly with other Google Cloud Platform services, making it ideal for modern app backends.

Ease of Deployment and Customer Service: Google Cloud Firestore is a managed service with straightforward deployment, comprehensive documentation, and full Google ecosystem support. Apache HBase requires intricate setup and maintenance for distributed environments, with support through community forums and paid options. Firestore provides a more user-friendly deployment experience.

Pricing and ROI: Apache HBase demands a significant upfront infrastructure investment for long-term scalability and cost efficiency. Google Cloud Firestore offers a predictable pay-as-you-go pricing model, leading to potentially faster ROI with manageable operational costs. The differentiation lies in HBase's upfront investment versus Firestore's cost-effective integrated services.

To learn more, read our detailed Apache HBase vs. Google Cloud Firestore Report (Updated: December 2025).

Buyer's Guide

Apache HBase vs. Google Cloud Firestore

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

Google Cloud Firestore

Ranking in NoSQL Databases

13th

Average Rating

8.4

Reviews Sentiment

5.4

Number of Reviews

Ranking in other categories

Managed NoSQL Databases (11th)

Mindshare comparison

As of January 2026, in the NoSQL Databases category, the mindshare of Apache HBase is 5.3%, up from 5.0% compared to the previous year. The mindshare of Google Cloud Firestore is 2.7%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

NoSQL Databases Market Share Distribution
Product	Market Share (%)
Apache HBase	5.3%
Google Cloud Firestore	2.7%
Other	92.0%

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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PrathapSankar

engagement Manager at Capgemini

Has simplified backend development for moderate user applications and supports efficient real-time data updates

A simplified way of building a logical layer on top of Firebase is necessary. Currently, the only option is to use cloud functions or Cloud Run functions. If they come up with an easier way of handling the logical layer between the frontend and backend, that would be beneficial. The UI of Firebase is much better compared to AWS or other Azure, but there is still scope for improving the usability of the UI. Additionally, some more AI features for automation can be added. The security layer can be enhanced, as currently, for data handling, there is just rule-based security; they can add one more layer of data security.

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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 most valuable part is the column family structure."

"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."

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

"The most valuable features are Firestore's query capabilities and its real-time syncing functionality."

"One of the main features of Google Cloud Firestore's document management is the real-time listener; whenever there are any changes in the data, all the documents and applications that are reading through that particular document get automatically notified that there was some change, and automatically all the data gets refreshed."

"I use the solution for maps, saving some locations, and chats."

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."

"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."

"Firestore needs improvements in its querying capabilities, particularly the ability to join tables and merge data from different tables before sending it to the front end."

"For lower volumes, it works fine, but once the volume increases, for use cases where the total number of users is less than 100,000 a month, Firebase is cheaper. But once you go beyond that, it becomes very expensive."

"I initially faced a problem creating groups in individual chats."

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Manufacturing Company

10%

University

Comms Service Provider

University

13%

Government

12%

Comms Service Provider

12%

Manufacturing Company

10%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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...

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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.

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What needs improvement with Google Cloud Firestore?

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What is your primary use case for Google Cloud Firestore?

Firebase is our main backend, so for managing authentications, for managing the backend database, and building cloud functions, it is all through Firebase. In the case of Google Cloud Firestore, th...

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What advice do you have for others considering Google Cloud Firestore?

I have experience with Firebase, especially Firebase, then Google Cloud Computing Engine, and then Google Firebase Studio. Google Cloud Firestore is one of the offerings in Firebase, which is basic...

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Compared 9% of the time

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Compared 6% of the time

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Compared 27% of the time

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Compared 13% of the time

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Compared 12% of the time

Redis vs Google Cloud Firestore

Compared 12% of the time

MongoDB Enterprise Advanced vs Google Cloud Firestore

Compared 12% of the time

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Product Reports

Buyer's Guide

NoSQL Databases

January 2026

Download Apache HBase product report

Buyer's Guide

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January 2026

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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

Google Cloud Firestore is a scalable, real-time NoSQL cloud database that provides document-oriented data storage and synchronizes data seamlessly across devices.

Designed for mobile, web, and server development, Firestore allows developers to store and sync data quickly. It supports real-time updates which enable your applications to reflect changes instantly. Firestore is based on a managed infrastructure, relieving developers from server-side maintenance and scalability concerns. It integrates with other Google Cloud services making it a convenient choice for modern app development.

What are the key features?

Real-Time Updates: Firestore automatically synchronizes data across all connected clients in real-time.
Scaling: Dynamically scales to accommodate growing data and user demands.
Offline Persistence: Stores data locally so that applications remain usable in offline mode.
Database Queries: Supports sophisticated queries to filter and retrieve data efficiently.
Security: Provides robust rules-based security for data control.

What benefits and ROI considerations should users review?

Improved Development Speed: Simplifies syncing and storing data, saving development time.
Cost-Effective: Pay-as-you-go pricing model ensures costs align with usage.
Efficiency: Reduced need for backend development enhances productivity.
Reliability: Rest assured with dependable infrastructure that ensures availability.

Firestore is widely used in industries like retail, where apps require real-time inventory tracking and customer insights. In health tech, it's utilized for patient data management, ensuring real-time updates across platforms while adhering to security protocols. Educational tech companies implement the database to provide an interactive learning experience with live collaboration features.

Google

Sample Customers

Bloomberg, Wells Fargo, Apple, Capital One, NVIDIA

Information Not Available

Buyer's Guide

Apache HBase vs. Google Cloud Firestore

December 2025

Free Report: Apache HBase vs. Google Cloud Firestore

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