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Apache HBase Reviews

Vendor: Apache
3.6 out of 5
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What is Apache HBase?

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.
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Apache HBase is the #10 ranked solution in top NoSQL Databases. PeerSpot users give Apache HBase an average rating of 7.2 out of 10. Apache HBase is most commonly compared to Redis: Apache HBase vs Redis. Apache HBase is popular among the large enterprise segment, accounting for 64% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 21% of all views.
Buyer's Guide
NoSQL Databases
August 2025
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Apache HBase mindshare

As of September 2025, the mindshare of Apache HBase in the NoSQL Databases category stands at 5.4%, up from 4.9% compared to the previous year, according to calculations based on PeerSpot user engagement data.
NoSQL Databases Market Share Distribution
ProductMarket Share (%)
Apache HBase5.4%
MongoDB Enterprise Advanced16.7%
ScyllaDB9.0%
Other68.9%
NoSQL Databases
 
 
Key learnings from peers

Valuable Features

Apache HBase offers a valuable column family structure and abstraction layer via Apache Phoenix, enabling SQL queries. Users benefit from its integration with Hadoop and HDFS, enhancing data storage and transport through pipelines. It excels in in-memory processing, optimizing queries with impressive speed, ideal for concurrent jobs and real-time aggregations. Linkage operations have minimal delay, making Apache HBase highly efficient and crucial for operations involving extensive data handling.
  • "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 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."

Room for Improvement

Apache HBase experiences performance issues with large data loads and increased regions, needing enhanced integration with Apache Phoenix and better resource optimization. Frequent problems occur during database requests and eligibility checks for credit, causing failure and hindering query resumption. Setup requires significant time due to network connectivity, often resulting in crashes. Improvements should reduce resource usage and ensure tasks continue seamlessly after interruptions.
  • "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."
  • "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."

Deployment

Users noted that deploying Apache HBase requires Apache Hadoop, which is complex due to numerous dependencies. Some found initial deployment straightforward, implementing it both on cloud platforms like AWS and on-premises. However, others encountered challenges, particularly with firewalls, leading to frequent problem-solving meetings. Participants in deployment processes highlighted varying experiences, indicating diverse levels of difficulty based on specific setup environments and requirements.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our NoSQL Databases Buyer's Guide for additional reliable information.

Top industries

By visitors reading reviews
Financial Services Firm
21%
Computer Software Company
9%
Manufacturing Company
7%
Educational Organization
7%
University
6%
Comms Service Provider
6%
Government
5%
Transportation Company
4%
Healthcare Company
3%
Outsourcing Company
3%
Media Company
3%
Wholesaler/Distributor
2%
Construction Company
2%
Energy/Utilities Company
2%
Insurance Company
2%
Legal Firm
2%
Non Profit
2%
Performing Arts
2%
Real Estate/Law Firm
2%
Recreational Facilities/Services Company
2%
Retailer
2%
Hospitality Company
1%
Renewables & Environment Company
1%
Aerospace/Defense Firm
1%
Marketing Services Firm
1%
Sports Company
1%
Museum Or Institution
1%
Training & Coaching Company
1%
Pharma/Biotech Company
1%
Logistics Company
1%

Compare Apache HBase with alternative products

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Learn more about Apache HBase

Apache HBase was previously known as HBase.

Apache HBase customers

Bloomberg, Wells Fargo, Apple, Capital One, NVIDIA

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NoSQL Databases

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Apache HBase Reviews Summary
Author infoRatingReview Summary
DevOps Engineer (M-PESA) at Safaricom Ethiopia plc4.0I've used Apache HBase mainly for customer data lookups and eligibility checks. It integrates well with Hadoop and Phoenix but needs better resource optimization during high loads. Overall, it's scalable, reliable, and suits our Big Data platform needs.
Principle Network and Database Engr at Parsons Corporation4.5I used Apache HBase for a year-long security system project and found it fast and efficient, though setup was time-consuming and network issues caused crashes. Support was excellent, and I’d rate it nine out of ten.
Principal Software Engineer at Securonix4.0We use Apache HBase for real-time data grouping, primarily appreciating its column family structure for real-time aggregations. However, we encounter performance issues when the number of regions increases, particularly under heavier loads.
Cloud and Big Data Engineer | Developer at Huawei Cloud Middle East2.0I use Apache HBase for managing consumer data sets due to its database capabilities. However, I face performance issues when storing large amounts of data. Despite these challenges, I have not considered other solutions or providers yet.