Apache Ignite 3 shows what really happens once your good enough multi-system setup starts cracking under high-volume load. This piece breaks down why the old stack stalls at scale and how a unified, memory-first architecture removes the latency tax entirely.
Discover how Apache Ignite 3 keeps related data together with schema-driven colocation, cutting cross-node traffic and making distributed queries fast, local and predictable.
Apache Ignite 3 is a memory-first distributed SQL database platform that consolidates transactions, analytics, and compute workloads previously requiring separate systems. Built from the ground up, it represents a complete departure from traditional caching solutions toward a unified distributed computing platform with microsecond latencies and collocated processing capabilities.
Apache Ignite 3.1 improves the three areas that matter most when running distributed systems: performance at scale, language flexibility, and operational visibility. The release also fixes hundreds of bugs related to data corruption, race conditions, and edge cases discovered since 3.0.
Apache Ignite 3.0 is the latest milestone in Apache Ignite evolution that enhances developer experience, platform resilience, and efficiency. In this article, we’ll explore the key new features and improvements in Apache Ignite 3.0.
We are happy to announce the release of Apache Ignite 2.17.0! In this latest version, the Ignite community has introduced a range of new features and improvements to deliver a more efficient, flexible, and future-proof platform. Below, we’ll cover the key highlights that you can look forward to when upgrading to the new release.
Old JDK code meets new Intel security feature, JVM + CLR in one process, and a mysterious crash.
As of December 25, 2023, Apache Ignite 2.16 has been released. You can directly check the full list of resolved Important JIRA tasks but let's briefly overview some valuable improvements.
Cache dumps
Ignite has persistent cache snapshots and this feature is highly appreciated by Ignite users. This release introduces another way to make a copy of user data - a cache dump.
The cache dump is essentially a file that contains all entries of a cache group at the time of dump creation. Dump is consistent like a snapshot, which means all entries that existed in the cluster at the moment of dump creation will be included in the dump file. Meta information of dumped caches and binary meta are also included in the dump.
Main differences from cache snapshots:
- Supports in-memory caches that a snapshot feature does not support.
- Takes up less disk space. The dump contains only the cache entries as-is.
- Can be used for offline data processing.
Dynamically building database queries can be necessary for some use cases, such as UI-defined filtering. This can get challenging with LINQ frameworks like EF Core and Ignite.NET.
As of April 26, 2022, Apache Ignite 2.13 has been released. You can directly check the full list of resolved Important JIRA tasks but here let's briefly overview some valuable improvements.
This is a breaking change release: The legacy service grid implementation was removed.
New Apache Calcite-based SQL engine
We've implemented a new experimental SQL engine based on Apache Calcite. Now it's possible to:
- Get rid of some H2 limitations;
- Optimize some query execution.
The current H2-based engine has fundamental limitations. For example:
- some queries should be splitted into 2 phases (map subquery and reduce subquery), but some of them cannot be effectively executed in 2 phases.
- H2 is a third-party database product with not-ASF license.
- The optimizer and other internal things are not supposed to work in a distributed environment.
- It's hard to make Ignite-specific changes to the H2 code, patches are often declined.