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  1. Stackups
  2. Application & Data
  3. In-Memory Databases
  4. In Memory Databases
  5. McRouter vs Redis

McRouter vs Redis

OverviewComparisonAlternatives

Overview

Redis
Redis
Stacks61.9K
Followers46.5K
Votes3.9K
GitHub Stars42
Forks6
McRouter
McRouter
Stacks20
Followers64
Votes0
GitHub Stars3.3K
Forks550

McRouter vs Redis: What are the differences?

Key Differences Between McRouter and Redis

1. Scalability and Performance: Mcrouter is specifically designed to handle the high-scale demands of large-scale Facebook applications, enabling horizontal scalability with its routing capabilities. It acts as a middle layer between clients and caches, effectively distributing the requests and reducing the load on individual servers. On the other hand, Redis is an in-memory data store that prioritizes fast data retrieval and is mainly used for caching, session storage, and real-time analytics in smaller-scale applications.

2. Flexibility and Data Structure Support: Redis provides an extensive set of data structures and features, including strings, lists, sets, hashes, sorted sets, and geospatial indexes. It allows users to perform operations on these data structures, making it a versatile choice for various use cases. Mcrouter, on the other hand, focuses on routing and cache management and does not offer the same breadth of data structure support as Redis.

3. Persistence and Durability: Redis offers both in-memory and persistent storage options, allowing the data to be saved to disk for durability. It provides various persistence mechanisms, such as snapshotting and append-only file (AOF) logs, ensuring that data is not lost during system failures. Mcrouter, being a routing layer, does not provide persistent storage capabilities and relies on the underlying caches for data persistence.

4. Replication and High Availability: Redis supports master-slave replication, enabling data to be replicated across multiple nodes for high availability and fault tolerance. It allows for automatic failover in case the master node goes down. Mcrouter, on the other hand, does not offer native replication capabilities. It primarily focuses on routing requests and load balancing across multiple cache instances.

5. Handling Complex Routing Logic: Mcrouter excels in handling complex routing logic with its advanced routing capabilities. It allows developers to define routing rules based on various criteria, including keys, prefixes, and regular expressions. This allows for fine-grained control over request routing and caching. Redis, on the other hand, does not provide such advanced routing features as it primarily focuses on data storage and retrieval.

6. Ecosystem and Community Support: Redis has a large and active community of developers, providing extensive documentation, tutorials, and support. It also has a wide range of client libraries available in different programming languages, making it easy to integrate with various applications. Mcrouter, being a Facebook-developed tool, has a relatively smaller community and may have limited third-party integrations and resources available compared to Redis.

In summary, Mcrouter is specifically designed for high-scale applications, offering advanced routing capabilities and easy integration with Facebook's cache infrastructure. On the other hand, Redis provides a versatile and feature-rich in-memory data store, suitable for various use cases with extensive community support.

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Detailed Comparison

Redis
Redis
McRouter
McRouter

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.

Mcrouter is a memcached protocol router for scaling memcached deployments. It's a core component of cache infrastructure at Facebook and Instagram where mcrouter handles almost 5 billion requests per second at peak.

-
Memcached ASCII protocol;Connection pooling;Multiple hashing schemes;Prefix routing;Replicated pools;Production traffic shadowing;Online reconfiguration;Flexible routing;Destination health monitoring/automatic failover;Cold cache warm up;Broadcast operations;Reliable delete stream;Multi-cluster support;Rich stats and debug commands;Quality of service;Large values;Multi-level caches;IPv6 support;SSL support
Statistics
GitHub Stars
42
GitHub Stars
3.3K
GitHub Forks
6
GitHub Forks
550
Stacks
61.9K
Stacks
20
Followers
46.5K
Followers
64
Votes
3.9K
Votes
0
Pros & Cons
Pros
  • 888
    Performance
  • 542
    Super fast
  • 514
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
Cons
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL
No community feedback yet
Integrations
No integrations available
Memcached
Memcached
HHVM (HipHop Virtual Machine)
HHVM (HipHop Virtual Machine)

What are some alternatives to Redis, McRouter?

Hazelcast

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.

Aerospike

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

MemSQL

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

Apache Ignite

Apache Ignite

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

SAP HANA

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

VoltDB

VoltDB

VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.

Tarantool

Tarantool

It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications

Azure Redis Cache

Azure Redis Cache

It perfectly complements Azure database services such as Cosmos DB. It provides a cost-effective solution to scale read and write throughput of your data tier. Store and share database query results, session states, static contents, and more using a common cache-aside pattern.

KeyDB

KeyDB

KeyDB is a fully open source database that aims to make use of all hardware resources. KeyDB makes it possible to breach boundaries often dictated by price and complexity.

twemproxy

twemproxy

twemproxy (pronounced "two-em-proxy"), aka nutcracker is a fast and lightweight proxy for memcached and redis protocol. It was built primarily to reduce the number of connections to the caching servers on the backend. This, together with protocol pipelining and sharding enables you to horizontally scale your distributed caching architecture.

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