Apache HBase vs. MongoDB

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
HBase
Score 7.3 out of 10
N/A
The Apache HBase project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable.N/A
MongoDB
Score 8.0 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0.10
million reads
Pricing
Apache HBaseMongoDB
Editions & Modules
No answers on this topic
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
HBaseMongoDB
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsFully managed, global cloud database on AWS, Azure, and GCP
More Pricing Information
Community Pulse
Apache HBaseMongoDB
Considered Both Products
HBase
Chose Apache HBase
Typically, Cassandra is faster on reads and HBase is faster on writes. You use Cassandra when you want to use a website, HBase is just an overall good general use database engine. Cassandra has its own storage engine and HBase uses HDFS and all its benefits. MongoDB is …
Chose Apache HBase
HBase is what you should use if you want a production ready scalable, JSON friendly, key-value, NoSQL, enterprise storage option. It excels over MongoDB due to integration with the extensive Hadoop stack and all the tools, frameworks and benefits there.

HBase has superior …
Chose Apache HBase
Compared NoSQL databases with traditional databases for faster retrieval and consistency. As MongoDB is a NoSQL supports dynamic fields, however, query performance is bad for aggregations and added maintenance. When compared with MySQL and Teradata, it could not scale up as …
Chose Apache HBase
These days I use Apache Cassandra more for even more scalability, good performance under different kind of workloads, and for providing highly available systems. Apache Cassandra also has connectors for Hadoop, Spark, and Solr.
MongoDB
Chose MongoDB
I use Cassandra more often these days for best in class performance, tunable consistency, linear scalability. In similar cases, I have used Apache HBase. But if there is a need for document store, MongoDB is the top choice.
Top Pros
Top Cons
Features
Apache HBaseMongoDB
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache HBase
7.7
5 Ratings
13% below category average
MongoDB
9.1
38 Ratings
4% above category average
Performance7.15 Ratings9.038 Ratings
Availability7.85 Ratings9.738 Ratings
Concurrency7.05 Ratings8.638 Ratings
Security7.85 Ratings8.638 Ratings
Scalability8.65 Ratings9.438 Ratings
Data model flexibility7.15 Ratings9.138 Ratings
Deployment model flexibility8.25 Ratings9.137 Ratings
Best Alternatives
Apache HBaseMongoDB
Small Businesses
IBM Cloudant
IBM Cloudant
Score 8.4 out of 10
IBM Cloudant
IBM Cloudant
Score 8.4 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 8.4 out of 10
IBM Cloudant
IBM Cloudant
Score 8.4 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 8.4 out of 10
IBM Cloudant
IBM Cloudant
Score 8.4 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HBaseMongoDB
Likelihood to Recommend
7.7
(10 ratings)
9.4
(78 ratings)
Likelihood to Renew
7.9
(10 ratings)
10.0
(67 ratings)
Usability
-
(0 ratings)
9.0
(14 ratings)
Availability
-
(0 ratings)
9.0
(1 ratings)
Support Rating
-
(0 ratings)
9.6
(13 ratings)
Implementation Rating
-
(0 ratings)
8.4
(2 ratings)
User Testimonials
Apache HBaseMongoDB
Likelihood to Recommend
Apache
Hbase is well suited for large organizations with millions of operations performing on tables, real-time lookup of records in a table, range queries, random reads and writes and online analytics operations. Hbase cannot be replaced for traditional databases as it cannot support all the features, CPU and memory intensive. Observed increased latency when using with MapReduce job joins.
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MongoDB
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
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Pros
Apache
  • Scalability. HBase can scale to trillions of records.
  • Fast. HBase is extremely fast to scan values or retrieve individual records by key.
  • HBase can be accessed by standard SQL via Apache Phoenix.
  • Integrated. I can easily store and retrieve data from HBase using Apache Spark.
  • It is easy to set up DR and backups.
  • Ingest. It is easy to ingest data into HBase via shell, Java, Apache NiFi, Storm, Spark, Flink, Python and other means.
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MongoDB
  • Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
  • You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
  • Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
Read full review
Cons
Apache
  • There are very few commands in HBase.
  • Stored procedures functionality is not available so it should be implemented.
  • HBase is CPU and Memory intensive with large sequential input or output access while as Map Reduce jobs are primarily input or output bound with fixed memory. HBase integrated with Map-reduce jobs will result in random latencies.
Read full review
MongoDB
  • An aggregate pipeline can be a bit overwhelming as a newcomer.
  • There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
  • Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
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Likelihood to Renew
Apache
There's really not anything else out there that I've seen comparable for my use cases. HBase has never proven me wrong. Some companies align their whole business on HBase and are moving all of their infrastructure from other database engines to HBase. It's also open source and has a very collaborative community.
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MongoDB
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
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Usability
Apache
No answers on this topic
MongoDB
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
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Support Rating
Apache
No answers on this topic
MongoDB
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
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Implementation Rating
Apache
No answers on this topic
MongoDB
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
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Alternatives Considered
Apache
Cassandra os great for writes. But with large datasets, depending, not as great as HBASE. Cassandra does support parquet now. HBase still performance issues. Cassandra has use cases of being used as time series. HBase, it fails miserably. GeoSpatial data, Hbase does work to an extent. HA between the two are almost the same.
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MongoDB
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
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Return on Investment
Apache
  • As Hbase is a noSql database, here we don't have transaction support and we cannot do many operations on the data.
  • Not having the feature of primary or a composite primary key is an issue as the architecture to be defined cannot be the same legacy type. Also the transaction concept is not applicable here.
  • The way data is printed on console is not so user-friendly. So we had to use some abstraction over HBase (eg apache phoenix) which means there is one new component to handle.
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MongoDB
  • Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
  • You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
Read full review
ScreenShots

MongoDB Screenshots

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