DBMS > Couchbase vs. Dgraph vs. PouchDB vs. Qdrant

System Properties Comparison Couchbase vs. Dgraph vs. PouchDB vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Distributed and scalable native Graph DBMS

JavaScript DBMS with an API inspired by CouchDB

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

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	1.28
Rank	#167	Overall
	#7	Vector DBMS

Website

www.couchbase.com

dgraph.io

pouchdb.com

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.couchbase.com

dgraph.io/docs

pouchdb.com/guides

qdrant.tech/documentation

Developer

Couchbase, Inc.

Dgraph Labs, Inc.

Apache Software Foundation

Qdrant

Initial release

2011

2016

2012

2021

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Go and Erlang

JavaScript

Rust

Server operating systems

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Docker
Linux
macOS
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

via views

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

JavaScript

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

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

View functions in JavaScript

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

yes

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Synchronous replication via Raft

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Planned for future releases

Key-based authentication

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