While working with big data, professionals often encounter the questions like which database is better. There is no specific answer to a question like this because a professional considers a lot of things when deciding the right type of technology that he or she wants to work with. The choices are sometimes a single Software and most of the times a combination that has worked well previously.
This blog is centered upon the use of Apache Cassandra with Zing. Now, Cassandra is a database management system (DBMS) established upon NoSQL. It has some unique features that can alleviate your routine data management experience. Zing on the other hand is a JVM designed to deliver high performance. Let’s look at the ways in which this combination can accelerate performance of your systems.
Known Issues in Cassandra
Cassandra and Zing complement each other or to say using Cassandra backed by Zing is sure to take care of all the loop holes that traditional Cassandra users have been encountering. There are two prominent issues that affect the performance.
- Memory Settings: Databases are meant for storing data and in Cassandra there are a few issues like setting limits for memtables to avoid running over the other important data. A lot of time and effort is required to continue monitor the memtables and then to set the limit so that these do not overrun the important information. Besides, the settings for heap are also at the maximum range which is above 90%. As a result, an out of memory error is thrown if the garbage collector fails to start.
- Garbage Collector Settings: In Cassandra, garbage collection triggers on the basis of the settings done by you. For example, you have set the heap threshold at 70%, so the garbage collection will kick off as soon as heap reaches that level. Similarly, Cassandra works with nodes which are interconnected and a problem with one node can cause garbage collector to pause. This can in return affect the entire cluster and be a big halt or a jolt for the system because such issues affect overall performance.
Perfect Solutions with Zing
The known issues in Cassandra are perfectly resolved when you use Zing and trust me the solutions are as simple as they can be. You do not have to put in any extra effort; but, just use Zing as the JVM instead of the one that you have been relying on. Let’s see how Zing solves the issues:
Zing’s ability to concurrently run garbage collector is the solution to the memory problems and all the pauses and halts that slows down the system. This is indeed a unique solution of big data services and miraculously it works. Zing claims to be an ideal solution for work requiring massive memory. The advantages certainly include faster processing, lower latency, guaranteed response time, etc. With such amazing advantages, Zing seems to be a perfect match for Cassandra.
Cassandra users would agree that it is a choice only because of the performance assured and that is why users would not hesitate to give Zing a try. Zing has been designed to aide Cassandra and deserves a trial. If you have been using Zing with Cassandra, share your experiences and suggestions in the comments section below.
