blocks|key|2204780|text|Redis和Hazelcast都是基于内存的数据库，因此在理论上，它们应该提供相同的速度和性能。查看Hazelcast的文档，您将获得更好的Redis支持，因为有大量用于与数据库接口的库。Hazelcast看起来只有java+lib，Redis对每种语言都有一个。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2204781|答案：|2204782|您将不得不自己测试这一点，据我所知，不同的比较表明Redis作为更快的其中一个在这里，但我不会说这些基准是100%25|ordered-list-item|offset|length|2204783|他们都应该是可靠的，但我不能担保哈泽尔卡斯特。|2204784|也许..。|2204785|我会使用Redis，因为我发现它是最有用的，而且它有很好的文档。|2204786|entityMap|0|LINK|mutability|MUTABLE|url|http://dormando.livejournal.com/525147.html^0|0|0|Z|7|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|X|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|Y|8|@]|9|@$G|Z|H|10|1|11]]|A|$]]|$1|I|3|J|5|F|7|12|8|@]|9|@]|A|$]]|$1|K|3|L|5|F|7|13|8|@]|9|@]|A|$]]|$1|M|3|N|5|6|7|14|8|@]|9|@]|A|$]]|$1|O|3|-4|5|6|7|15|8|@]|9|@]|A|$]]]|P|$Q|$5|R|S|T|A|$U|V]]]]

Both Redis and Hazelcast are memory based databases, so in theory, they should provided the same speed and performance. Looking over the docs for Hazelcast, you will get better support with Redis because of the wide amount of Libraries for interfacing with the database. Hazelcast looks like they only have java libs, Redis has one for every language.

Answers:

<ol>
<li>You will have to test this on your own, as far as I can tell different comparisons shows Redis as faster <a href="http://dormando.livejournal.com/525147.html" rel="nofollow">one of them is here</a>, but i won't say these benchmarks are 100%</li>
<li>They should be both reliable, but I can not vouch for Hazelcast.</li>
<li>Maybe...</li>
</ol>

I would go with Redis, because I find it is the most usable and it has great documentation.

blocks|key|2204788|text|为了满足缓存需求，我们从redis切换到hazelcast。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2204789|对我们来说，预言片%2B黑兹尔广播比我们快得多。|unordered-list-item|2204790|预言片%2B+Jedis+(合并)%2B+Redis|2204791|我们使用原型来序列化那些创建成本很高的bean。Hazelcast标准序列化机制要慢得多.我们的环境是玻璃鱼3.1。|2204792|Hazelcast看起来只有java+lib，Redis对每种语言都有一个。|blockquote|2204793|是真的。Hazelcast只提供了REST和memcached协议的实现。|2204794|entityMap^0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|P|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|Q|8|@]|9|@]|A|$]]|$1|E|3|F|5|D|7|R|8|@]|9|@]|A|$]]|$1|G|3|H|5|6|7|S|8|@]|9|@]|A|$]]|$1|I|3|J|5|K|7|T|8|@]|9|@]|A|$]]|$1|L|3|M|5|6|7|U|8|@]|9|@]|A|$]]|$1|N|3|-4|5|6|7|V|8|@]|9|@]|A|$]]]|O|$]]

We switched from redis to hazelcast for our caching needs.

<ul>
<li>Protostuff + Hazelcast
is much faster for us than</li>
<li>Protostuff + Jedis (pooled) + Redis</li>
</ul>

We use protostuff to serialize beans that are expensive to create. Hazelcasts standard-serialization mechanism is much slower. Our environment is Glassfish 3.1.

<blockquote>
 Hazelcast looks like they only have java libs, Redis has one for every language.
</blockquote>

True. Hazelcast provides just a REST API and an implementation of the memcached protocol.

blocks|key|651134|text|有一个非常方便的库-+雷迪森。它提供分布式Java对象和服务(BitSet、BloomFilter、Set、SortedSet、Map、ConcurrentMap、List、Queue、Deque、BlockingQueue、BlockingDeque、ReadWriteLock、Semaphore、d14、AtomicLong、CountDownLatch、Publish+/+Subscribe、RemoteService、ExecutorService、LiveObjectService、d21)！|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|651135|它支持集群、哨兵、主/从和单连接模式。|651136|完美地在云中工作，并支持AWS弹力缓存和Azure+Redis+cloud|651137|以下是Redisson客户的一些成功案例：|651138|从哈泽尔卡斯特搬到雷迪斯|651139|使用Redis+(从Hazelcast迁移)的分布式锁定|651140|请注意:我是“Redisson”的作者|651141|entityMap|0|LINK|mutability|MUTABLE|url|https://redisson.org/|1|https://engineering.datorama.com/moving-from-hazelcast-to-redis-b90a0769d1cb|2|https://carlosbecker.com/posts/distributed-locks-redis/^0|V|6|12|B|1E|3|1I|9|1S|3|1W|D|2A|4|2F|5|2L|5|2R|D|35|D|3J|D|3X|9|47|2V|B|3|0|0|0|J|0|0|11|0|0|L|0|0|C|0|C|1|0|0|S|0|S|2|0|0|J|0^^$0|@$1|2|3|4|5|6|7|13|8|@$9|14|A|15|B|C]|$9|16|A|17|B|C]|$9|18|A|19|B|C]|$9|1A|A|1B|B|C]|$9|1C|A|1D|B|C]|$9|1E|A|1F|B|C]|$9|1G|A|1H|B|C]|$9|1I|A|1J|B|C]|$9|1K|A|1L|B|C]|$9|1M|A|1N|B|C]|$9|1O|A|1P|B|C]|$9|1Q|A|1R|B|C]|$9|1S|A|1T|B|C]|$9|1U|A|1V|B|C]]|D|@$9|1W|A|1X|1|1Y]]|E|$]]|$1|F|3|G|5|6|7|1Z|8|@$9|20|A|21|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|22|8|@$9|23|A|24|B|C]]|D|@]|E|$]]|$1|J|3|K|5|6|7|25|8|@$9|26|A|27|B|C]]|D|@]|E|$]]|$1|L|3|M|5|6|7|28|8|@$9|29|A|2A|B|C]]|D|@$9|2B|A|2C|1|2D]]|E|$]]|$1|N|3|O|5|6|7|2E|8|@$9|2F|A|2G|B|C]]|D|@$9|2H|A|2I|1|2J]]|E|$]]|$1|P|3|Q|5|6|7|2K|8|@$9|2L|A|2M|B|C]]|D|@]|E|$]]|$1|R|3|-4|5|6|7|2N|8|@]|D|@]|E|$]]]|S|$T|$5|U|V|W|E|$X|Y]]|Z|$5|U|V|W|E|$X|10]]|11|$5|U|V|W|E|$X|12]]]]

There is a very handy lib - <a href="https://redisson.org" rel="nofollow noreferrer">Redisson</a>. It provides distributed Java objects and services (<code>BitSet</code>, <code>BloomFilter</code>, <code>Set</code>, <code>SortedSet</code>, <code>Map</code>, <code>ConcurrentMap</code>, <code>List</code>, <code>Queue</code>, <code>Deque</code>, <code>BlockingQueue</code>, <code>BlockingDeque</code>, <code>ReadWriteLock</code>, <code>Semaphore</code>, <code>Lock</code>, <code>AtomicLong</code>, <code>CountDownLatch</code>, <code>Publish / Subscribe</code>, <code>RemoteService</code>, <code>ExecutorService</code>, <code>LiveObjectService</code>, <code>ScheduledExecutorService</code>) on top of Redis server!
It supports cluster, sentinel, master/slave and single connection modes.
Perfectly works in cloud and supports AWS Elasticache and Azure Redis Cloud
Below are some success stories from Redisson customers:
<a href="https://engineering.datorama.com/moving-from-hazelcast-to-redis-b90a0769d1cb" rel="nofollow noreferrer">Moving from Hazelcast to Redis</a> 
<a href="https://carlosbecker.com/posts/distributed-locks-redis/" rel="nofollow noreferrer">Distributed Locking with Redis (Migration from Hazelcast)</a>
Please note: I'm an author of Redisson

blocks|key|2204884|text|到2017年，Redis和Hazelcast都提供了高度可用的\可伸缩的key\value存储。非常快的响应时间&；10。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2204885|Redis的独特之处在于它支持其他数据结构，如删失集、散列集和pub\sub机制。它还可以通过lua脚本进行扩展。这可能是这两种产品中最受欢迎和最广泛使用的。尤其是在Java生态系统之外。|2204886|Hazelcast的独特之处在于它可以嵌入到Java主机进程中，这使得它很适合在不依赖外部数据库的情况下构建有状态的微服务。它还存在其他一些小的差异，比如从密钥到期时获得回叫的能力。从某种意义上说，它做的总体上较少，但它所做的事情很少，它做得更好。尤其是如果你在使用Java。|2204887|总的来说，这些解决方案都是为类似的用例设计的，例如缓存外部数据，为有状态的微服务创建通信后台或共享内存状态，甚至可能存储(少量的非关系)业务数据，具有一定的持久性。|2204888|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|L|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|M|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|I|$]]

As of 2017, both Redis and Hazelcast offer highly available\scalable key\value storage. With very fast response times &lt; 10ms.

Redis is unique in that it supports other data structures like sored sets, hash sets and a pub\sub mechanism. It's also extensible via lua scripting. It is probably the most popular and widely used of the two products. Especially outside of the Java ecosystem.

Hazelcast is unique in that it can be embedded in a Java host process, making it great for building stateful microservices without an external database dependency. It also has some other small differences, like the ability to get a call back from a key expiration. In a sense, it does less overall but the few things it does, it does them better. Especially if you're using Java.

Overall these are similar solutions designed for similar use cases like caching external data, creating a communication backplane or shared memory state for a stateful microservice, or possibly even storing (small amounts of non-relational) business data with some degree of durability.

blocks|key|2204899|text|要确定哪一个是好的，有一个关于客户端线程使用的问题。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2204900|根据这个基准测试，如果您使用更多的线程，则Hazelcast比Redis更好。也许这是一个不公平的公司基准，但显示了一些线程。|offset|length|2204901|entityMap|0|LINK|mutability|MUTABLE|url|http://blog.hazelcast.com/redis-vs-hazelcast-radargun-puts-them-to-a-challenge/^0|0|4|4|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|O|8|@]|9|@$D|P|E|Q|1|R]]|A|$]]|$1|F|3|-4|5|6|7|S|8|@]|9|@]|A|$]]]|G|$H|$5|I|J|K|A|$L|M]]]]

To decide which one is the good, there is an issue about the client-thread using. 

According to this <a href="http://blog.hazelcast.com/redis-vs-hazelcast-radargun-puts-them-to-a-challenge/" rel="nofollow noreferrer">benchmark</a> Hazelcast is better than Redis if you use more thread. Maybe this is an unfair company benchmark but shows something about threading.

Redis Vs Hazelcast
If my app:

<ul>
<li>Have a lot of http requests (6,000 per minute, I collect clicks info) that needs to be saved</li>
<li>Have a lot of http requests that query the data previously saved.</li>
</ul>

My Questions are
- Which one between Redis and Hazelcast should I chose to store and query data
- which one is faster for reads and writes?
- which one is more reliable?
- Might Cassandra be a better option?

Answering any of the questions helps

redis vs hazelcast

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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如果我的应用程序: Redis与Hazelcast：有很多需要保存的http请求(每分钟6,000次，我收集点击信息)有很多查询以前保存的数据的http请求。我的问题是--在Redis和Hazelcast之间，我应该选择哪一个存储和查询数据--哪个数据读写速度更快?哪个更可靠？--卡桑德拉( Cassandra )是否...

问redis诉hazelcast
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