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

Mongoose vs Redis

OverviewComparisonAlternatives

Overview

Redis
Redis
Stacks61.9K
Followers46.5K
Votes3.9K
GitHub Stars42
Forks6
Mongoose
Mongoose
Stacks2.4K
Followers1.4K
Votes56

Mongoose vs Redis: What are the differences?

<Write Introduction here>
  1. Data Structure: Mongoose is an Object Data Modeling (ODM) library for MongoDB and provides a schema-based solution to model data whereas Redis is an in-memory data store that primarily uses key-value pairs to store data.

  2. Persistence: Mongoose is typically used for persisting data in a database like MongoDB which provides persistent data storage across restarts, while Redis can be used as a caching layer or an in-memory database that may not persist data beyond the lifetime of the application unless configured with persistence settings.

  3. Query Language: Mongoose uses JavaScript-based query language that closely resembles MongoDB's query language, making it easy for developers familiar with MongoDB to work with. On the other hand, Redis offers a different set of commands and data structures for querying and manipulating data compared to traditional databases like MongoDB.

  4. Scalability: Redis is known for its high performance and ability to handle large volumes of data in memory efficiently, making it a popular choice for applications that require fast data access and high scalability. While Mongoose is focused on modeling data structures and interacting with MongoDB, which might not offer the same level of scalability as Redis in certain use cases.

  5. Use Cases: Mongoose is commonly used in applications that require a schema-based data modeling approach and complex data relationships, often seen in web applications or APIs that need structured data storage. Redis, on the other hand, is preferred for scenarios where fast data access, caching, and temporary data storage are crucial, such as real-time analytics, session management, and message queues.

  6. Durability: In terms of durability, Mongoose provides ACID transactions and durable data storage capabilities when used with MongoDB, ensuring data consistency and reliability. Redis, on the other hand, focuses more on performance and speed, which may compromise durability in certain scenarios unless specific persistence configurations are implemented.

In Summary, Mongoose and Redis differ in their data structure, persistence, query language, scalability, ideal use cases, and durability, catering to different needs in terms of data modeling and storage solutions for applications.

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Detailed Comparison

Redis
Redis
Mongoose
Mongoose

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.

Let's face it, writing MongoDB validation, casting and business logic boilerplate is a drag. That's why we wrote Mongoose. Mongoose provides a straight-forward, schema-based solution to modeling your application data and includes built-in type casting, validation, query building, business logic hooks and more, out of the box.

Statistics
GitHub Stars
42
GitHub Stars
-
GitHub Forks
6
GitHub Forks
-
Stacks
61.9K
Stacks
2.4K
Followers
46.5K
Followers
1.4K
Votes
3.9K
Votes
56
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
Pros
  • 17
    Well documented
  • 17
    Several bad ideas mixed together
  • 10
    JSON
  • 8
    Actually terrible documentation
  • 2
    Recommended and used by Valve. See steamworks docs
Cons
  • 3
    Model middleware/hooks are not user friendly
Integrations
No integrations available
Node.js
Node.js
MongoDB
MongoDB

What are some alternatives to Redis, Mongoose?

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.

Mongoid

Mongoid

The philosophy of Mongoid is to provide a familiar API to Ruby developers who have been using Active Record or Data Mapper, while leveraging the power of MongoDB's schemaless and performant document-based design, dynamic queries, and atomic modifier operations.

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