DBMS > ArcadeDB vs. Couchbase vs. JanusGraph vs. PlanetScale

System Properties Comparison ArcadeDB vs. Couchbase vs. JanusGraph vs. PlanetScale

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Document store

Graph DBMS

Relational DBMS

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

Document store
Spatial DBMS

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Website

Technical documentation

Developer

Arcade Data

Couchbase, Inc.

Linux Foundation; originally developed as Titan by Aurelius

PlanetScale

Initial release

2021

2011

2017

2020

Current release

September 2021

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

0.6.3, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C, C++, Go and Erlang

Java

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

SQL-like query language, no joins

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

yes

with proprietary extensions

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Java

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Clojure
Java
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

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

yes

proprietary syntax

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency
Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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.

User authentification and security via Rexster Graph Server

Users with fine-grained authorization concept

no user groups or roles

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