DBMS > Postgres-XL vs. RethinkDB vs. SpaceTime vs. SwayDB vs. Vitess

System Properties Comparison Postgres-XL vs. RethinkDB vs. SpaceTime vs. SwayDB vs. Vitess

Editorial information provided by DB-Engines

Name

Description

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.

SpaceTime is a spatio-temporal DBMS with a focus on performance.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

Relational DBMS

Document store
Spatial DBMS

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

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.postgres-xl.org

rethinkdb.com

www.mireo.com/spacetime

swaydb.simer.au

vitess.io

Technical documentation

www.postgres-xl.org/documentation

rethinkdb.com/docs

vitess.io/docs

Developer

The Linux Foundation

since July 2017

Mireo

Simer Plaha

The Linux Foundation, PlanetScale

Initial release

2014

since 2012, originally named StormDB

2009

2020

2018

2013

Current release

10 R1, October 2018

2.4.1, August 2020

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Mozilla public license

Open Source

Apache Version 2

commercial

Open Source

GNU Affero GPL V3.0

Open Source

Apache Version 2.0, commercial licenses available

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++

Scala

Server operating systems

Linux
macOS

Linux
OS X
Windows

Linux

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

schema-free

yes

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

yes

distributed, parallel query execution

A subset of ANSI SQL is implemented

yes

with proprietary extensions

APIs and other access methods

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

RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.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

C#
C++
Python

Java
Kotlin
Scala

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

user defined functions

yes

proprietary syntax

Triggers

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

range based

Fixed-grid hypercubes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Real-time block device replication (DRBD)

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

MVCC

Atomic single-document operations

Atomic execution of operations

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

table locks or row locks depending on storage engine

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

yes

Users with fine-grained authorization concept

no user groups or roles

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More resources

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