Since the arrival of Apache Cassandra in the scene of businesses, small, medium, and even large companies have pounded on the opportunity of grabbing it. Quite accurately, the Apache Cassandra Developers enjoyed the NoSQL Database, no single point of failure(SPOF), huge amount of nodes and data handling ability. These were obvious reasons to fall in love with Apache Cassandra and integrate it in businesses. However, Cassandra is not an ideal choice for each and every business project on this planet!
Apache Cassandra Consulting Companies have faced a huge difference in working with SQL and NoSQL databases. Apart from that, Cassandra contains tables with their individual keys, surprisingly without relations! These factors compel Apache Cassandra Developers to make certain mistakes creating havoc. In this blog, we will discuss the 8 common mistakes when using Apache Cassandra.
8 Common Mistakes You Should Avoid When Using Apache Cassandra
These mistakes are usually for both Apache Cassandra Developers and Businesses, when they start judging the book by its cover. Let’s unveil the book and read it carefully to avoid these mistakes in the future.
Apache Cassandra is well-known to be a relying wall for business giants like Amazon and Walmart. Therefore, companies with a huge amount of data are tempted to integrate Cassandra in their business structure. This is where the first mistake when using Cassandra hits hard. Cassandra should not be used as a general data store that holds a large amount of data. In fact, Cassandra’s optimization for fast reads of large amounts of data allow it to achieve the feat.
As we already discussed, Cassandra cannot be embedded in every business use case. However, if you are aware of using perfectly and not getting influenced by other companies, Cassandra has a lot to offer!
- Quick Default Setting Change
Remember when people used mobile phones for the first time back in the days, they immediately switched to settings and implemented changes. Well, the trend is still going on, but this time it’s Cassandra bearing the arrows. Apache Cassandra Developers try to change the settings once they start using the database, that can certainly increase the latency speed. Appropriately, they should get well-versed with the database at first and then start making changes.
Getting well-versed will include understanding data modelling approach, client application usage, historical trends, and consequences on the cluster. Once these understandings are clear and transparent, feel free to make the changes!
- Starting With Domain Model Implementation
While having a chat with Apache Cassandra Development Companies, we came to know that many developers start with implementing domain models in the very beginning. Although it’s a genuine process when you are working with SQL databases, Cassandra is a NoSQL database. Therefore, starting with domain model implementation can be a tedious task.
What you should do is start with queries instead! Understanding the access patterns will help you a lot in the long run.
- Is Cassandra A Relational Database?
Having a knowledge of the database you are working in is one aspect, but adapting to the situation is another crucial aspect when working with a database. Similarly, when Cassandra is handled by developers with relational database background, they tend to use the feature of multiple writes by creating access patterns. What it does is allow data duplication which has to be processed beforehand.
The constant updation and processing affects the speed of the database, altering the overall performance. Therefore, Apache Cassandra is not a Relational Database and should not be used as one.
- Query Through Data Would Be A Mountain To Climb
Creating a query through the available data is another tedious task that developers often commit. Again, the task is a cakewalk when using SQL databases, but Cassandra is a NoSQL database. The equality comparisons performed by partition key and clustering key prevents the query through data. This means that you cannot add filter features to a column using other columns.
However, new versions have started using keywords to allow filtering, but it won’t be recommended for an effective use of Cassandra database.
No one would deny that Cassandra is a powerful database more than capable of overcoming network partitions and other changes. However, it doesn’t indicate that you should leave the database on its own. Most Apache Cassandra Developers fail to monitor the database on a regular basis. Contrastingly, Cassandra requires 24×7 monitoring due to both external and internal changes.
Performance indicators such as disc usage, latency, throughput, and others are essential for optimal deployment. Therefore, they should be continuously monitored by the developers.
Size and quantity are two crucial factors when considering hardware for your database. Normally, Cassandra deals with huge amounts of data, developers prefer large hardwares in a small quantity. What it does is extends the compactions process and delays the speed of the database, for which Cassandra is known for. Apart from that, it increases the garbage collection, as well. Therefore, having small nodes in a large quantity is always the best hardware type for Cassandra.
Last but not least, Apache Cassandra Developers tend to overlook the security features of the database. After production and deployment of packers on schedule, they lay less attention to the security. Obviously, security is essential to protect intricate and valuable data from outrageous threats. For this, patching Apache Cassandra with a production environment should be a necessity. It will ensure security at all stages of the deployment process.
Learning From The Mistakes!
These were the 8 common mistakes developers often make when working with Cassandra. Well, this gives us an insight into what not to do while handling the NoSQL database. If you are looking for someone to blindly lay down your confidence and expect them to avoid these mistakes, Ksolves is an appropriate option for you. We are an Apache Cassandra Consulting Company with Cassandra Consultants carrying ample experience in their bag. Our customer-driven approach helps us to consolidate our customized solutions in the best use of our customers. Contact us to learn more about our Apache Cassandra Development Company!
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AUTHOR
Apache Cassandra
Anil Kushwaha, Technology Head at Ksolves, is an expert in Big Data and AI/ML. With over 11 years at Ksolves, he has been pivotal in driving innovative, high-volume data solutions with technologies like Nifi, Cassandra, Spark, Hadoop, etc. Passionate about advancing tech, he ensures smooth data warehousing for client success through tailored, cutting-edge strategies.
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