Cassandra has become the talk of the Big Data community. The Cassandra database is the right option for the database for scalability and high availability without compromising performance for mission-critical applications. Heavy-load applications such as Netflix and Facebook are solely dependent on Cassandra because of the features offered. Cassandra’s USPs, such as excellent performance, scalability, and resilient database quality, make it extremely easy to master and handles complex applications with great ease.
Features of Cassandra that make it stand out
Cassandra can store large volumes of operational data. It also offers a platform for back-end development and analysis of the collected data. With tonnes of features, Cassandra is creating wonders in the Big Data industry.
Let’s have a look:
1. Scalable Architecture
Cassandra enables you to increase capacity and scalability linearly by simply adding more nodes to the cluster. With this, there is an immediate increase in response time and throughput. This database follows peer-to-peer architecture instead of master-slave architecture. Cassandra can scale horizontally by adding more data centers or vertically by adding more nodes.
2. Support different sets of Data Structures
Many businesses use Cassandra for applications where data grows in an unbounded direction instantly. This database supports all types of data structures. Apart from this, it also helps the dynamic changes to the data structures which reflect the changing needs.
3. Seamless Distribution
When dealing with a large set of data, Cassandra has proven the place to be excellently reliable. With the simple process of data replication, It distributes the data over multiple data centers in a seamless manner. For applications, losing data is not affordable as it means losing time and money to restore or recover information that is essential to your business.
4. High-speed Data Writes
Without affecting read efficiency, Cassandra lets you store a massive amount of data. It is truly fast as the data are written in Cassandra has a swift pace to store it on hardware or cloud. File distribution in Cassandra is peer-to-peer across all the nodes, which makes the data distributed all over the set of nodes in the cluster. Irrespective of data residing in the cluster or not, the nodes available in the cluster accept a request for writing and reading data.
Today in the world, there is a massive amount of data that has to be validated and to be updated as soon as possible. If the data found is not the most recent, Cassandra returns the newest value of the data, and the outdated data is revised to keep the system updated. One real-life example is the cricket score. Here, the data is generated on every ball thrown, i.e., scores are being revised to keep the system updated which is effortlessly taken care of by Cassandra.
5. High Availability and Fault Tolerance
Cassandra is highly available and fault-tolerant because of data replication. This means, if one node fails, the data is readily available in different nodes. Therefore, we can retrieve the data from those nodes. The user sets a number of replications. According to that number, you can replicate each row in a cluster based on the row key. Data replication can be across multiple data centers that can eventually lead to recovery competencies and a high level back up.
6. Time to Live (TTL) concept
The Time to Live concept is one of the features of Cassandra, which is a clear way to tell how long the data is valid or terminate the data when it is of no longer use. This kind of database itself supports purging; there is no need to write a separate scheduler to delete this kind of data.
Real-Life Use Case Example
One of the best use case examples is health management apps. Nowadays, everyone uses health apps, which have a health-fitness tracker and all the medical data of the person. Such domains capture data like step counts, heartbeats, pulses, etc. which belong to unstructured data types that can be stored in Cassandra. This data is being saved to the remote server so that it can be used for analytics.
The above-mentioned features make Cassandra stand out from the crowd of already-established big data technology. Application with a large amount of data that want back-end development and analysis of the collected data can preferably choose Cassandra.
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