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Redis

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Redis vs Zookeeper: What are the differences?

Introduction:

Redis and Zookeeper are two popular open-source technologies used for handling distributed data processing and coordination in large-scale systems. Although they serve different purposes, there are key differences between the two.

  1. Data Structure and Storage: Redis is primarily an in-memory data store that supports a wide range of data structures, including strings, hashes, lists, sets, and sorted sets. It offers persistence by periodically saving data to disk. On the other hand, Zookeeper is a distributed coordination service that provides a hierarchical data model similar to a file system, allowing clients to store and retrieve data in a tree-like structure called znodes.

  2. Consistency Model: Redis offers eventual consistency, where updates to the data may take some time to propagate across all replicas. It allows users to choose between different replication models, including asynchronous and synchronous replication. In contrast, Zookeeper provides strong consistency guarantees. It ensures that all clients will observe the same order of updates and that all updates will be reflected in the system within a known time frame.

  3. Primary Use Cases: Redis is commonly used as a high-performance cache, message broker, and data structure server for real-time applications. It excels in scenarios that require fast read and write operations on small to medium-sized datasets. Zookeeper, on the other hand, is primarily used for distributed coordination tasks such as leader election, distributed locking, and configuration management. It provides a reliable and highly available centralized service for coordination across multiple systems.

  4. Concurrency Control: Redis supports optimistic concurrency control through optimistic locking mechanisms like Multi-Version Concurrency Control (MVCC). It relies on users to handle conflicts and provides commands for atomic operations on multiple keys. In contrast, Zookeeper provides distributed coordination primitives like locks, barriers, and queues, ensuring mutual exclusion, synchronization, and sequencing of events among multiple processes.

  5. Support for Watchers: Redis offers an event notification mechanism called "pub/sub" that allows clients to subscribe to specific channels and receive updates in real-time. While it provides a basic form of notification, it lacks more advanced features like conditional event triggering or filtering based on data changes. Zookeeper, on the other hand, provides powerful watchers that allow clients to be notified of changes to znodes, enabling reactive programming and efficient event-driven processing.

  6. Scalability and Fault Tolerance: Redis supports horizontal scalability through sharding, allowing data to be distributed across multiple nodes. It provides mechanisms for replication, failover, and automatic partitioning. Zookeeper is designed to provide high availability and fault tolerance by using a replicated ensemble of servers. It ensures that a majority of servers need to be available to maintain service availability and data consistency.

In summary, Redis is a versatile in-memory data store that excels in high-performance caching and real-time applications, while Zookeeper is a distributed coordination service focused on providing strong consistency and coordination primitives for complex distributed systems.

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Pros of Redis
Pros of Zookeeper
  • 886
    Performance
  • 542
    Super fast
  • 513
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
  • 194
    Open source
  • 182
    Easy to deploy
  • 164
    Stable
  • 155
    Free
  • 121
    Fast
  • 42
    High-Performance
  • 40
    High Availability
  • 35
    Data Structures
  • 32
    Very Scalable
  • 24
    Replication
  • 22
    Great community
  • 22
    Pub/Sub
  • 19
    "NoSQL" key-value data store
  • 16
    Hashes
  • 13
    Sets
  • 11
    Sorted Sets
  • 10
    NoSQL
  • 10
    Lists
  • 9
    Async replication
  • 9
    BSD licensed
  • 8
    Bitmaps
  • 8
    Integrates super easy with Sidekiq for Rails background
  • 7
    Keys with a limited time-to-live
  • 7
    Open Source
  • 6
    Lua scripting
  • 6
    Strings
  • 5
    Awesomeness for Free
  • 5
    Hyperloglogs
  • 4
    Transactions
  • 4
    Outstanding performance
  • 4
    Runs server side LUA
  • 4
    LRU eviction of keys
  • 4
    Feature Rich
  • 4
    Written in ANSI C
  • 4
    Networked
  • 3
    Data structure server
  • 3
    Performance & ease of use
  • 2
    Dont save data if no subscribers are found
  • 2
    Automatic failover
  • 2
    Easy to use
  • 2
    Temporarily kept on disk
  • 2
    Scalable
  • 2
    Existing Laravel Integration
  • 2
    Channels concept
  • 2
    Object [key/value] size each 500 MB
  • 2
    Simple
  • 11
    High performance ,easy to generate node specific config
  • 8
    Java
  • 8
    Kafka support
  • 5
    Spring Boot Support
  • 3
    Supports extensive distributed IPC
  • 2
    Curator
  • 2
    Used in ClickHouse
  • 2
    Supports DC/OS
  • 1
    Used in Hadoop
  • 1
    Embeddable In Java Service

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Cons of Redis
Cons of Zookeeper
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL
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    What is Redis?

    Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

    What is Zookeeper?

    A centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. All of these kinds of services are used in some form or another by distributed applications.

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    What are some alternatives to Redis and Zookeeper?
    Memcached
    Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    RabbitMQ
    RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
    Hazelcast
    With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.
    Cassandra
    Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
    See all alternatives