Cassandra vs Hbase – What’s the Difference (Pros and Cons)
Cassandra vs Hbase – What’s the Difference (Pros and Cons). In this blog, we are going to discuss the two most popular database management systems, Cassandra and Hbase and look into how they compare against each other.
It is very significant to select an effective and streamlined database management system that makes the app development process effortless and even provides a successful end result. However, the selection process is not as straightforward as you think. You have to consider numerous details while choosing the appropriate system. Most probably the one that gives the impactful performance of your project as well as the development process.
Let’s have a look at Cassandra vs Hbase – What’s the Difference (Pros and Cons).
What Is Cassandra
Apache Cassandra is considered the NoSQL system class that is designed for creating the most reliable and scalable data array repositories, represented as the hash. It includes key spaces that are positioned with the concept of a database schema in the relational model. It also provides several column facilities related to a relational table.
Features of Apache Cassandra
Apache Cassandra provides its users with the following features:
Open Source – Prices of a product plays a very crucial role in our life. Cassandra is that database management system that is not only powerful and reliable but also completely free. Its open source feature enabled the users to create a vast Cassandra Community to discuss all the problems and queries.
Peer to Peer Architecture – In Cassandra, some database works on master slave while some work on peer to peer. The master slave architecture contains the main unit, with which the rest communicate. On the other hand, peer to peer architecture constitutes multiple units that communicate with each other. Hence, it eliminates any point of failure.
Scalable – Cassandra allows its users to scale up and scale down Cassandra cluster effortlessly. It provides flexibility while adding or deleting any number of nodes from the cluster without disturbances. Because of its scalability feature, Cassandra is known for its high throughput for the highest number of nodes.
High Availability and Fault Tolerance – Data replication means storing data in several locations. It makes Cassandra highly available and fault tolerant. It means that when one node fails, the user can access data in different nodes.
Performance – Cassandra database provides the best performance. It enables the developers to utilize the capabilities of several multi core machines.
Pros of Apache Cassandra
Highly Efficient – Cassandra is a highly efficient database management system. It is designed to exploit the hidden capabilities of specific multi core machines.
Column Oriented – Cassandra is column oriented. The Cassandra caches column is based on column names that provide immediate cut. While traditional databases contain column names that include data, Cassandra’s column name constitutes actual data.
Provides Adjustable Consistency – Cassandra enables its user to arbitrarily adjust data consistency in nodes. It saves the copies of data on every node and even allows users to customize those copies.
Schema less – Cassandra’s column is the weight of the user’s choice in rows. It model is the only model that is known as an optional schema model.
Cons of Apache Cassandra
- It does not provide ACID and relational data properties.
- It also does not support aggregates.
- When you make multiple requests and read more data, the actual transactions slow down, thereby resulting in latency problems.
- It models data around queries instead of its structure. That is why the same data is stored several times.
- The reads in Cassandra are relatively slow.
What is Hbase
Hbase is a distributed, scalable and column based database management system that includes a dynamic diagram for structured data. With the help of this system, users can efficiently manage a large number of data sets distributed among several servers.
Features of Hbase
- It is linearly scalable.
- It delivers reads and writes consistently.
- It provides an effortless java API for clients.
- It provides data replication across clusters.
- It has automatic failure support.
- It integrates with Hadoop as a source as well as a destination.
Pros of Hbase
- Provide Large Data Sets – Hbase is capable of handling large datasets on top of HDFS file storage. It also aggregates and analyzes several rows present in the Hbase table.
- Fast Processing – Data reading and processing in Hbase can be performed within a small amount of time.
- Scalabile – Hbase supports both modular and linear forms of scalability.
- Consistent– Users, who look for high speed requirements use Hbase as it offers consistent reads and writes.
- Schema less – it does not support fixed column schema. It only defines column families.
Cons of Hbase
- When the user uses only one Hmaster, the possibility of failure increases.
- Hbase does not support transactions.
- It does not include permission or built in authentication.
- Since it does not support SQL structure, users cannot use any query optimizer.
- Hbase time memory issues on the cluster are integrated with Pig and Hive job results.
- When the user integrates with Map reduce jobs, they have to face unpredictable latencies.
Cassandra vs Hbase - Key Differences
The key differences between Cassandra and Hbase:
Infrastructure
Hbase uses Hadoop infrastructure, consisting of several moving parts like Zookeeper, Hbase master, Data nodes and name nodes. On the other hand, Cassandra uses different infrastructure and operations. It also uses different DBMS along with its infrastructure.
Support
Hbase does not support ordered partitioning. However, it offers a coprocessor capability that supports triggers. It serves a single row by using one region server at a time. On the contrary, Cassandra supports ordered partitioning that makes the row size up to 10’s megabytes. However, it creates hot spots for its users. Moreover, Cassandra supports range based row scams.
Nodes
Users using Cassandra have to identify nodes as seed nodes, a point used for inter cluster communication. However, Hbase constitutes master nodes that monitor and coordinates the action of region servers.
Internode Communication
Both Cassandra and Hbase include internode communication. However, Cassandra uses Gossip Protocol for it. It helps in transferring data from one node to another. In short, it replicates the data. However, Hbase relies on the Zookeeper protocol. Here, the other nodes get the data from the main node.
Transactions
Cassandra includes lightweight transactions. This transaction uses “Compare and Set” and “Row Level Write Isolation.” On the contrary, Hbase includes two mechanisms for these transactions. It constitutes the “Check and Put” and Read Check Delete” mechanism.
Query Language
Both Hbase and Cassandra shells are based on the JRuby shells. However, Cassandra uses a specific Query Language and CQL, which is modeled after SQL.
Documentation
Cassandra’s documentation is far better than Hbase’s documentation. The documentation makes working and learning effortless for Cassandra users.
Bloom Filter
Hbase uses a bloom filter as indexing. It provides asynchronous replication of the cluster as the storage unit all across the WAN. On the other hand, Cassandra uses bloom filters for key lookup. Its random partitioning provides row replication across a WAN.
Great! You have learned about Cassandra vs Hbase – What’s the Difference (Pros and Cons).
Cassandra vs Hbase – What’s the Difference Conclusion
These differences between Cassandra and Hbase show that Hbase is more like a meta data storage as it depends on third party systems. It also becomes a little complex since an independent system requires more resources. While Hbase is used for storing small information in large databases, Cassandra is suitable for large scale data storage and ingestion. Cassandra is best for real time transaction processing and interactive data. On the other hand, Hbase is appropriate for performing aggregations on big data.
Why don’t you take a look at Cassandra alternatives and their pros: Redis, MongoDB, PostgreSQL or Apache Kafka.
