Apache Ignite Reviews & Product Details

Apache Ignite's standout feature lies in its In-Memory Data Grid (IMDG). This powerful capability allows you to store and process large datasets in-memory across a distributed cluster of servers. By keeping frequently accessed data in-memory, Ignite significantly boosts data access speed, leading to enhanced application performance.

In a real-life scenario, imagine a large-scale e-commerce platform experiencing high traffic during a flash sale. Apache Ignite could be employed as a distributed caching solution. Frequently accessed product data, pricing information, and user preferences are stored in-memory across a cluster of servers. This optimizes response times for product searches, reduces database load, and ensures a seamless shopping experience for users during peak demand periods. The distributed nature of Ignite helps distribute the load, preventing bottlenecks and improving overall system performance during such events. Review collected by and hosted on G2.com.

Potential drawback of Apache Ignite is that it might not be the best fit for simple or small-scale projects. The overhead associated with setting up and managing a distributed system could outweigh the benefits in scenarios where a more straightforward caching solution or database might suffice. Careful consideration of the project's scale and requirements is essential to determine if Apache Ignite is the most suitable choice. Review collected by and hosted on G2.com.

I am truly impressed with Apache Ignite's exceptional performance and scalability. The seamless integration and robust features have significantly enhanced our operations. The ease of use has streamlined our processes, allowing for efficient data management and retrieval. Apache Ignite has proven to be a powerful solution that meets and exceeds our expectations, making it an invaluable asset to our projects. Review collected by and hosted on G2.com.

While Apache Ignite has been a valuable addition to our toolkit, there are a few areas that could benefit from improvement. One aspect that I find challenging which has occasionally impacted the overall user experience. Additionally, [mention any other dislikes], and addressing these areas could enhance the usability and overall satisfaction with the platform. Despite these challenges, I believe Apache Ignite has great potential, and I look forward to seeing future updates that address these concerns Review collected by and hosted on G2.com.

The main thing which I like about the Apache ignite is that it is a high perfomant system. Also it allows users to build applications which can expand horizontakly Review collected by and hosted on G2.com.

In a tech perspective what I would say as a dislike would be the documentation. It could have been alittle more convenient for the learning curve Review collected by and hosted on G2.com.

The main think I liked from ignite is high performance and it is horizontally scalable. Review collected by and hosted on G2.com.

For a dislike if I say something that is the documentation, because it has to be more convenient. Review collected by and hosted on G2.com.

Ignite is one of the best in business. Easy to use and highly recommended. Review collected by and hosted on G2.com.

Nothing as of sort. All of the features are up to mark. Although lil change in GUI could make it more easier to use. Review collected by and hosted on G2.com.

Easy to handle large datasets and provides collocation feature to improve the query performance. Review collected by and hosted on G2.com.

JVM should be configured properly otherwise system will get hang up and performance will be degraded. Review collected by and hosted on G2.com.

Apache Ignite along with its caching capabilities provide full support to Cassandra. Which helped our developers to write easy and distributed joins. We are still not production, so we will understand its capabilities when we go distributed. Review collected by and hosted on G2.com.

Currently, any numeric datatype requires value as zero, forcing us to migrate all our data and then adding in the field to an existing table. Too much setup is required to run in the case of Spring Boot Applications. Review collected by and hosted on G2.com.

Since all data in Ignite is off heap you can expect very nice GC profile if you can keep your allocation rates modest. BinaryObject API is useful since you read a field without full object deserialisation and you do not need domain classes present on servers' classpath. Review collected by and hosted on G2.com.

Since data is off heap, Ignite has to serialise and deserialise all the data you will be accessing from the application code. Ignite will synchronise the partitions, but the operation is expensive. If you have a solution where there is transactional replicated caches with strong read write consistency, you will pay a great cost for keeping the cluster synchronised. Ignite has to be load tested after each iteration and the design tuned a lot to keep it performant. Review collected by and hosted on G2.com.

I love how easy to use the Apache Ignite API is, it's very intuitive and allows me to create a resilient distributed in-memory cache which is lightning fast. I really appreciate the quality of the documentation, taught me a lot! Review collected by and hosted on G2.com.

When I last used it, the ignite-zookeeper library was lagging behind the official zookeeper version significantly. I see that's changed a bit now, but still lagging a little (3.4.13 vs 3.5.6). However, the curator dependency is still severely outdated (2.9.1 vs 4.2.0). I needed to shade these in order to make progress on my distributed service. Review collected by and hosted on G2.com.