DBMS > CouchDB vs. Manticore Search vs. MongoDB vs. Qdrant vs. RavenDB

System Properties Comparison CouchDB vs. Manticore Search vs. MongoDB vs. Qdrant vs. RavenDB

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Multi-storage database for search, including full-text search.

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

A high-performance vector database with neural network or semantic-based matching

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Graph DBMS
Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

couchdb.apache.org

manticoresearch.com

www.mongodb.com

github.com/qdrant/qdrant
qdrant.tech

ravendb.net

Technical documentation

docs.couchdb.org/en/stable

manual.manticoresearch.com

www.mongodb.com/docs/manual

qdrant.tech/documentation

ravendb.net/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Manticore Software

MongoDB, Inc

Qdrant

Hibernating Rhinos

Initial release

2005

2017

2009

2021

2010

Current release

3.3.3, December 2023

6.0, February 2023

6.0.7, June 2023

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GPL version 2

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

Apache Version 2.0

Open Source

AGPL version 3, commercial license available

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Erlang

C++

Rust

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

schema-free

Fixed schema

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

schema-free

Typing

predefined data types such as float or date

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

Numbers, Strings, Geo, Boolean

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Can index from XML

Secondary indexes

yes

via views

yes

full-text index on all search fields

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

SQL-like query language

Read-only SQL queries via the MongoDB Atlas SQL Interface

SQL-like query language (RQL)

APIs and other access methods

RESTful HTTP/JSON API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

JavaScript

yes

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Synchronous replication based on Galera library

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Collection-level replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency, tunable consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

atomic operations within a single document possible

yes

isolated transactions for atomic changes and binary logging for safe writes

Multi-document ACID Transactions with snapshot isolation

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

optional, enabled by default

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

Access rights for users can be defined per database

Access rights for users and roles

Key-based authentication

Authorization levels configured per client per database

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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