DBMS > ArcadeDB vs. Postgres-XL vs. RethinkDB vs. Typesense

System Properties Comparison ArcadeDB vs. Postgres-XL vs. RethinkDB vs. Typesense

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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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Document store

Search engine

Secondary database models

Document store
Spatial DBMS

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	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.79
Rank	#210	Overall
	#14	Search engines

Website

Technical documentation

docs.arcadedb.com

www.postgres-xl.org/documentation

rethinkdb.com/docs

typesense.org/docs

Developer

Arcade Data

The Linux Foundation

since July 2017

Initial release

2021

2014

since 2012, originally named StormDB

2009

2015

Current release

September 2021

10 R1, October 2018

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Mozilla public license

Open Source

Apache Version 2

Open Source

GPL V3

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

Java

C++

Server operating systems

All OS with a Java VM

Linux
macOS

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

distributed, parallel query execution

APIs and other access methods

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

Supported programming languages

Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

MVCC

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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More resources

DB-Engines blog posts

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