Atomix
Redisson
Our great sponsors
Atomix | Redisson | |
---|---|---|
1 | 3 | |
2,343 | 22,706 | |
-0.1% | 1.3% | |
2.2 | 9.9 | |
20 days ago | 2 days ago | |
Go | Java | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Atomix
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How to Achieve Geo-redundancy with Zeebe
To understand how we can achieve resilience in Zeebe, you first need to understand how Zeebe does replication. Zeebe uses distributed consensus — more specifically theRaft Consensus Algorithm — for replication.There is an awesomevisual explanation of the Raft Consensus Algorithm available online, so I will not go into all the details here. The basic idea is that there is a single leader and a set of followers. The most common setup is to have one leader and two followers, and you’ll see why soon.
Redisson
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Kotlin Spring WebFlux, R2DBC and Redisson microservice in k8s 👋✨💫
Source code you can find in the GitHub repository. he main idea of this project is the implementation of microservice using Kotlin, Spring WebFlux, PostgresSQL, and Redis with metrics and monitoring and deploying it to k8s. For interacting with PostgresSQL we will use reactive Spring Data R2DBC and for Redis caching using Redisson.
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Am I overlooking any potential issues that could arise from my implementation?
I came up empty handed in search of an alternative to Quartz for scheduling Crons in a clustered/distributed environment. Redisson has a scheduler, but it came with its own issues: - https://github.com/redisson/redisson/issues/4020 - https://github.com/redisson/redisson/issues/3991 - https://github.com/redisson/redisson/issues/4321
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Implement Hibernate 2nd level Cache with Redis, Spring Boot, and Spring Data JPA
4. We use the open-source library Redisson to connect to Redis instance and use Redis as Hibernate 2nd level cache. Please see their Github repo for more information.
What are some alternatives?
Hazelcast - Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.
Jedis - Redis Java client
Apache ZooKeeper - Apache ZooKeeper
Akka - Build highly concurrent, distributed, and resilient message-driven applications on the JVM
Ehcache - Ehcache 3.x line
JGroups - The JGroups project
Chronicle Map - Replicate your Key Value Store across your network, with consistency, persistance and performance.
Vert.x - Vert.x is a tool-kit for building reactive applications on the JVM
MapDB - MapDB provides concurrent Maps, Sets and Queues backed by disk storage or off-heap-memory. It is a fast and easy to use embedded Java database engine.
ScaleCube - Microservices library - scalecube-services is a high throughput, low latency reactive microservices library built to scale. it features: API-Gateways, service-discovery, service-load-balancing, the architecture supports plug-and-play service communication modules and features. built to provide performance and low-latency real-time stream-processing