Apache Cassandra database is a popular system created for the management of high volumes of structured data on commodity servers. It has a unique distributed architecture. The data can be placed on separate machines with over one factor for replication. The advantages here are that the data can be available everywhere, and failures are not limited to a single point.
Now, if you scrutinize Apache Cassandra, you will find that it is a query language that more or less is the same as the SQL language. The methods for data modeling, however, are entirely different. If you are not careful and create a wrong data model, the performance of the system fails. This commonly occurs when the end-user tries to incorporate the concepts of the RDBMS system on Apache Cassandra. To avoid this issue, it is prudent to keep in mind the following rules-
Note, when you are using Apache Cassandra, the writes are generally not expensive. However, it does not support the OR clause; support joins, group by, etc. You need to store the information to make it retrievable. The following rules will come in handy-
- The writes here are quite cheap, and you can optimize the system for high-quality writing performance. Make sure you maximize the writes for improved read performance and the availability of data. You will find a tradeoff between data read and data write here. Make sure you maximize the performance of data read by optimizing the number or the volume of data writes.
- Optimize data duplication- Data duplication or data denormalization must be optimized in Apache Cassandra. The disk space is cheaper than the operation of the CPU processing, memory, and IOs operations. Since Apache Cassandra is a unique distributed database, data duplication ensures you promptly get data availability and no risks of data failures from a single point.
Origins of Apache Cassandra
The following are some salient facts about the origins of Apache Cassandra-
- Cassandra was developed for inbox search at Facebook
- Facebook made it into the open-sourced system in 2008
- Apache incubator took over Cassandra in 2009
- It is one of the top-level projects of Apache since 2010
- Apache Cassandra 3.2.1 is the latest version
NoSQL Databases include Cassandra
NoSQL databases are also known as Non-Relational Databases or Not Only SQL systems. They store and can retrieve data except for tabular relations like relational databases. They include Cassandra, HBase, and MongoDB. Given below are the salient traits of NoSQL databases-
- The design is simple ‘
- Uses horizontal scaling
- The availability of the data is high
The data structure that Cassandra uses is more specified over other data structures found in relational databases. They are faster over them.
You will find NoSQL databases’ presence, especially in Big Data and web applications, in real-time. They are often called Not Only SQL databases because they might support SQL similar query language too.
Comparison between the Relational and NoSQL Cassandra Database
Professionals from the reputed database management company, RemoteDBA lays down the following comparison between Relational and NoSQL databases
|Manages influx of data at low velocities||Manages the influx of data at high velocity|
|Data comes in from single and few locations||Data comes in from multiple locations|
|Complex transactions that have joined are supported||Simple transactions are supported|
|There is single or one point of failure||There is no single or one point of failure|
|Manages moderate volumes of data||Manages high volumes of data|
|Deployments are centralized||Deployments are decentralized|
|Transactions are written in a single location||Transactions are written in several locations|
|Get read scalability||Gives write and read scalability|
|Can be deployed in a vertical fashion||Can be deployed in a horizontal fashion|
Features of Apache Cassandra
Given below are the standard features of Apache Cassandra-
- The architecture can be scaled massively- The system is simple to operate and is very easy for you to scale. The design is high in quality. The nodes are at the same levels.
- You can write and read data at all nodes
- The performance of the database improves when you add more nodes to the system.
- If a node fails, they can be restored and later recovered
- The data model can be both dynamic and flexible. The datatypes can have fast read and write.
- You can protect the data with a committed log design. You can create a security build-in with the restore and backup mechanisms.
- You get outstanding support for consistency of data via a distributed architecture
- You get the unique feature under Cassandra to replicate data over several data centers.
- You get the advantages of compressing 80% of the data without any overhead costs
- The Query Language here is like the SQL language. This makes it simple for developers of relational databases to move to a Cassandra database with success.
When you choose an excellent database for your business, you must keep your budget, the salient needs of the business, and the advantages of the database system to meet the goals of your business in mind. Apache Cassandra is a fantastic database for businesses that offer messaging services and deal with mobile phones. These companies deal with massive amounts of data, and so Cassandra is the perfect database for them. It is suitable for applications that receive data at great speed from sensors and devices. It provides eCommerce businesses with reliable protection for shopping carts.
The input and output for product catalogs are faster. This is why retail apps widely prefer it. The database also helps social media service providers and other digital companies offer recommendations and analysis. It is a fantastic database for them. If your business deals with large volumes of data, this database is perfect for your needs and you can get great benefits out of it. Ensure you have the right professionals to deal with its support, security, and performance to enjoy maximum benefits with success!