Top Apache Ignite Alternatives

Companies often face a challenge while trying to find a good platform that can help them handle their application databases in an effective manner, which can be absolutely huge in some cases. They find this in the Apache Ignite, which can processes such databases easily through distributive computing. It has several advantages over competitors regarding speed, stability, and scalability.

Faster processing of big data

Along with the management of large application databases, the Ignite platform can also be used as a tool for big data analysis and processing. It is actively recommended by top companies using big data analysis for their daily procedures. Data sets from various query and database software can be integrated into the Ignite databases for the best and the fastest results. Operations like MapReduce are accelerated to an extreme degree, almost nearing 100 times the normal speed. This allows the presentation of highly accurate analysis and operation results in mere seconds to minutes for routine procedures.

State-of-the-art techniques for quicker results

Ignite has a very powerful advantage over other distributed databases. This advantage lies in the fact that it uses several techniques to optimize processing. For example, from a storage point-of-view, it uses a memory-based approach by default, instead of a disk-based approach. What improves by doing that is the speed of processing, which does so at an exponential rate. While this means that the storage will be partial in the case of some of the larger databases, this problem can be easily rectified as well by the use of additional clusters. Also, even the computation takes data from memory. 

Easy and cheap implementation and maintenance

Distributed computing with Ignite is quite easy to implement and cheap to maintain. Rather than using one single costly system, Ignite uses several nodes of computing hardware at once. It is not only cost-effective but also increases reliability. Companies can easily upscale their architecture by increasing memory of each node, and data gets backed up on each node's storage just in case. Maintenance is also easier as teams can be set for the cleanup and maintenance of each node.