HBase vs Cassandra

Definition of HBase vs Cassandra

HBase vs Cassandra architecture is different, but both contain NoSQL databases. Basically, HBase architecture is designed to support data management, whereas Cassandra architecture supports management and data storage without relying on other systems. Hbase uses a master-based architecture with a single point of failure, whereas Cassandra uses a masterless architecture. We can say that HBase is a high-consistency data storage system.

Difference between HBase vs Cassandra

In HBase, we store data in a column fashion by using frequent attributes that we keep as quick access. Apache Cassandra is an example of a key-value store that contains ordered column entries. Hbase writes data to a single data server, whereas Cassandra writes data to multiple data servers and versions. In comparison to Cassandra, read access to HBase is more accessible.

Hbase stores data in HDFS, which provides block caches and faster read performance. Whereas Cassandra needs to check the partition table data to find the node where it was stored. We need to scan the data to use the non-partition or secondary key to find the data.

What is HBase?

The HBase model is used to provide random access for the structured data which contains large in amount. The HBase builds on the top of the hadoop file system and it will be column oriented in nature. We are using HBase to store the data HDFS.

HBase is an open-source database that provides replication. HBase contains main three components i.e. Zookeeper, region server, and HMaster. Basically, HBase is a column-based, scalable, and distributed database system.

What is Cassandra?

Basically, Cassandra is designed to handle a large amount of data across multiple nodes. Cassandra provides high availability without any failure. Cassandra has a distributed architecture that can handle large amounts of data. To achieve high availability, we place data on multiple machines using more than one replication factor.

Cassandra is a NoSQL system that was designed for creating data array repositories that were represented by hash. Cassandra normally works with the key space, which is responsible for aligning the database schema concept with the relational model.

Head to Head Comparison Between HBase vs Cassandra (Infographics)

Below are the top 14 differences between HBase vs Cassandra:

Key Differences between HBase vs Cassandra

Let us look at the key differences between HBase and Cassandra:

Cassandra writes the log and cache simultaneously, whereas in HBase we cannot write concurrently. While writing in the log and cache decreases the writing speed, so it will make Cassandra write slower as compared to HBase.

The latency is HBase and Cassandra is defined as the delay between the commencement of data transfer and transfer instruction. The latency of HBase decreases by using random reads and it updates while latency will increases.

Throughput is defined as the number of operations measures across for accessing the performance of machines. HBase is showing the throughout as constant, whereas Cassandra contains a rise throughout.

We are observing average read latency higher in HBase as compared to Cassandra. But this latency is not varying more by using increases in the number of reading operations.

HBase architecture is basically designed to support data management. HBase contains the following components.

• HMaster
• Hregionmaster
• Hregions
• Zookeeper
• HDFS

Cassandra architecture supports management and data storage. Cassandra contains the following components.

• Node
• Replication factor
• Partitioner
• SStable
• Memtable
• Cluster
• Commit log

HBase is a consistent data store that allows the architecture of master and slave, which is used at the time of failure. Cassandra focuses on availability which falls behind in consistency.

HBase Requirement

As we know that HBase uses different types of caches for filling the memory. Commvault supports Cloudera and distributions of hortonworks of the apache hadoop by using simple and Kerberos authentication. To install the Hbase we required the following hardware as follows.

• Installing Hbase on Linux operating system is the best practice.
• To install the HBase we require a minimum of 1 GB of disk space, below 1 GB we cannot install the HBase software.
• We can also check the requirement of disk space at the time of installation.
• To store the log of HBase we require a minimum of 500 MB of free disk space.
• To install the HBase we need to create a separate user for hadoop.
• Also, we need to install the java version on 1.7+.
• We also need to install and configure the HDFS.

Cassandra Requirement

Below are the software and hardware requirements at the time of using Cassandra in our system. As we know that Cassandra is highly concurrent and able to handle multiple requests by using multiple threads. Below is the requirement of Cassandra as follows.

• To install the Cassandra we require a minimum of 4 GB RAM
• Cassandra supports Linux operating system.
• We require 2 cores or above CPU while using Cassandra.
• At the time of installing Cassandra first, we need to install JDK 1.7+ version in our system.
• At the time of installing Cassandra first, we need to install the python 2.7+ version in our system.
• At the time of installing Cassandra first, we need to install the DataStax enterprise max 5.1.0+ version in our system.
• The index data center node requires a minimum of 300 GB of space.
• Message data center node requires 5 TB space.
• We need to configure the NTP protocol.

Comparison Table of HBase vs Cassandra

The table below summarizes the comparisons between HBase vs Cassandra:

HBase	Cassandra
HBase uses the infrastructure of the hadoop framework.	Cassandra employs the DBMS and makes use of the infrastructure of multiple applications.
HBase is based on the model of master-slave architecture.	Cassandra is based on an active-active model.
HBase is based on Google BigTable.	Cassandra is basically based on the AWS Dynamo DB.
HBase does not support ordered partitioning.	Cassandra supports ordered partitioning.
HBase accessibility cluster depends on the availability of the master node.	In Cassandra all nodes are equal.
HBase provides more consistency as compared to Cassandra.	Cassandra provides less consistency as compared to HBase.
HBase contains the ability for using a co-processor.	Cassandra does not contain the ability for using a co-processor.
A trigger supports the HBase model.	A trigger does not support the Cassandra model.
HBase supports the custom-based language.	Cassandra supports the CQL.
HBase is not easy to learn as compared to Cassandra.	Cassandra is easy to learn as compared to HBase.
The setup of a cluster in HBase is not easy as compared to Cassandra.	The setup of a cluster in Cassandra is easy as compared to HBase.
HBase supports automatic rebalancing.	Cassandra also supports the feature of automatic rebalancing.
HBase provides two methods for handling transactions.	Cassandra also provides two methods for handling transactions.
HBase is good for intensive reads as compared to Cassandra.	Cassandra is good at writing as compared to HBase.

Purpose of HBase

Basically, HBase is an open-source and distributed database that was based on Google’s big table. Hbase is built onto the top of HDFS, it is borrowing several features of the big table like compression and in-memory operation. Hbase is using HDFS as a distributed file system. It will allow the database to store large datasets which contained billions of rows.

Hbase is supporting the sparse data along with the fact it was distributed across with hardware of a commodity server, which is cost-effective. The common use case of HBase is including the hadoop distribution and log analytics.

Purpose of Cassandra

Cassandra uses masterless architecture which provides multiple benefits to the architecture of master and slave. Cassandra contains the active-active architecture which means all the node of the cluster is treated equally and node majority is used to achieve the quorum. Cassandra stores data in the row and column format.

Cassandra provides agility in the sense that allows rows in different columns which was allowing changes in the column format. Cassandra uses CQL, so it is easy for SQL users to understand quickly. Cassandra offers a repair process for read and write operations.

Conclusion

HBase stores data in the HDFS which provides block caches and faster performance for reading. Whereas Cassandra needs to check the partition table data for finding the node where it was stored. HBase contains the master-based architecture which contains the single point of failure, while Cassandra architecture is masterless.

Recommended Articles

This is a guide to HBase vs Cassandra. Here we discuss HBase vs Cassandra key differences with infographics and a comparison table in detail. You can also go through our other suggested articles to learn more –

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