System architects closely monitor usage patterns of their application to identify any increase or decrease in load on their systems. It varies drastically over holidays or weekdays or any occasional event, depending on the nature of the business. This challenges the IT infrastructure to be as robust as possible, to manage user growth and the subsequent network and processing load, so to scale up or down as per requirement.
Scaling means to be able to either add or remove application servers depending on the load. Adding application servers (scaling up) helps to maintain throughput rate on heavy loads whereas removing servers from the cluster (scaling down) helps to keep server uptime costs in check when they are being underutilized.
Web apps are always built to handle this kind of unpredictability, i.e. keeping in mind the scalability requirements of the business. But in this otherwise scalable architecture, your relational database becomes a bottleneck when you add more user load to your application. Due to this, many system architects consider using a NoSQL database since it provides scalability.
On the other hand, replacing your relational database with a NoSQL database is almost impossible in a majority ofcases. The reason is simple. Relational databases have an established ecosystem whose benefits outweigh any scalability gains you’ll get by replacing them. It just involves too much time and cost to make it happen. But, don’t feel bad. There is another where you can have your cake and eat it too.
What I mean is: You can continue using your relational databases and resolve the scalability bottleneck along the way. The answer to your needs is an In-Memory NoSQL datastore. This store does not persist information on hard disk and instead keeps it all in memory (RAM).
The best thing about it: In-Memory NoSQL datastore supplements the architecture and doesn’t replace it. It is architected for high availability and high scalability. Frequently used data is kept in this store and ‘write calls’ can be asynchronously transferred to the database thus improving the performance.
TayzGrid is an In-Memory NoSQL store that is extremely fast and scalable. The main advantage of having an In-Memory NoSQL datastore like TayzGrid is that it can scale very well by distributing its data across different servers. This allows it to reduce the heavy load from the database, complete distribution of data and respond to requests faster since the data is in RAM. An In-Memory NoSQL datastore doesn’t only provide the ability to easily scale your application but it also gives a major boost to your application performance, allowing you to maintain high throughput in high usage scenarios.
In-Memory NoSQL data stores like TayzGrid can be used through the popular JCache API (JSR 107) which has standards on using an In-Memory NoSQL store. As a result, you are not locked into one vendor and can seamlessly switch to different JCache compliant solutions. TayzGrid is 100% JCache compliant.
In conclusion, if you’re looking to scale your application without having to disrupt your production flow then an In-Memory NoSQL store is the way to go. It removes all the RDBMS bottlenecks, and on top of it, it also provides high availability for your application.
TayzGrid is an OpenSource Java based in-Memory NoSQL datastore. It is free to download and use and is under the Apache 2.0 License. It has been developed by the makers of NCache, and has a variety of features and options.