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  1. Stackups
  2. Application & Data
  3. Databases
  4. Odm
  5. Mongoose vs RocksDB

Mongoose vs RocksDB

OverviewComparisonAlternatives

Overview

Mongoose
Mongoose
Stacks2.4K
Followers1.4K
Votes56
RocksDB
RocksDB
Stacks141
Followers290
Votes11
GitHub Stars30.9K
Forks6.6K

Mongoose vs RocksDB: What are the differences?

Developers describe Mongoose as "MongoDB object modeling designed to work in an asynchronous environment". 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. On the other hand, RocksDB is detailed as "Embeddable persistent key-value store for fast storage, developed and maintained by Facebook Database Engineering Team". RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.

Mongoose belongs to "Object Document Mapper (ODM)" category of the tech stack, while RocksDB can be primarily classified under "Databases".

"Well documented" is the primary reason why developers consider Mongoose over the competitors, whereas "Very fast" was stated as the key factor in picking RocksDB.

Mongoose and RocksDB are both open source tools. Mongoose with 19K GitHub stars and 2.63K forks on GitHub appears to be more popular than RocksDB with 14.3K GitHub stars and 3.12K GitHub forks.

PedidosYa, Accenture, and WebbyLab are some of the popular companies that use Mongoose, whereas RocksDB is used by Facebook, LinkedIn, and Skry, Inc.. Mongoose has a broader approval, being mentioned in 88 company stacks & 92 developers stacks; compared to RocksDB, which is listed in 6 company stacks and 7 developer stacks.

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Detailed Comparison

Mongoose
Mongoose
RocksDB
RocksDB

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.

RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.

-
Designed for application servers wanting to store up to a few terabytes of data on locally attached Flash drives or in RAM;Optimized for storing small to medium size key-values on fast storage -- flash devices or in-memory;Scales linearly with number of CPUs so that it works well on ARM processors
Statistics
GitHub Stars
-
GitHub Stars
30.9K
GitHub Forks
-
GitHub Forks
6.6K
Stacks
2.4K
Stacks
141
Followers
1.4K
Followers
290
Votes
56
Votes
11
Pros & Cons
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
Pros
  • 5
    Very fast
  • 3
    Made by Facebook
  • 2
    Consistent performance
  • 1
    Ability to add logic to the database layer where needed
Integrations
Node.js
Node.js
MongoDB
MongoDB
No integrations available

What are some alternatives to Mongoose, RocksDB?

MongoDB

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.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

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.

Memcached

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.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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