DBMS > Amazon Redshift vs. OrigoDB vs. RethinkDB vs. Splice Machine vs. SwayDB

System Properties Comparison Amazon Redshift vs. OrigoDB vs. RethinkDB vs. Splice Machine vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A fully ACID in-memory object graph database

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

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

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Document store

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

origodb.com/docs

rethinkdb.com/docs

splicemachine.com/how-it-works

Developer

Amazon (based on PostgreSQL)

Robert Friberg et al

The Linux Foundation

since July 2017

Splice Machine

Simer Plaha

Initial release

2012

2009

under the name LiveDB

2009

2014

2018

Current release

2.4.1, August 2020

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

AGPL 3.0, commercial license available

Open Source

GNU Affero GPL V3.0

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

C++

Java

Scala

Server operating systems

hosted

Linux
Windows

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

.NET Client API
HTTP API
LINQ

JDBC
Native Spark Datasource
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net

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++
Java
JavaScript (Node.js)
Python
R
Scala

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Java

Triggers

yes

Domain Events

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

range based

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

depending on model

yes

Transaction concepts

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

ACID

Atomic single-document operations

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

yes

users and table-level permissions

Access rights for users, groups and roles according to SQL-standard

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