DBMS > Amazon Redshift vs. NSDb vs. RDFox vs. RethinkDB vs. RocksDB

System Properties Comparison Amazon Redshift vs. NSDb vs. RDFox vs. RethinkDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

High performance knowledge graph and semantic reasoning engine

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

aws.amazon.com/redshift

nsdb.io

www.oxfordsemantic.tech

rethinkdb.com

rocksdb.org

Technical documentation

docs.aws.amazon.com/redshift

nsdb.io/Architecture

docs.oxfordsemantic.tech

rethinkdb.com/docs

github.com/facebook/rocksdb/wiki

Developer

Amazon (based on PostgreSQL)

Oxford Semantic Technologies

The Linux Foundation

since July 2017

Facebook, Inc.

Initial release

2012

2017

2009

2013

Current release

6.0, Septermber 2022

2.4.1, August 2020

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Scala

C++

Server operating systems

hosted

Linux
macOS

Linux
macOS
Windows

Linux
OS X
Windows

Linux

Data scheme

yes

RDF schemas

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes

string, binary, float, bool, date, geometry

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

restricted

all fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

APIs and other access methods

JDBC
ODBC

gRPC
HTTP REST
WebSocket

RESTful HTTP API
SPARQL 1.1

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

Java
Scala

C
Java

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++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

replication via a shared file system

Source-replica replication

yes

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

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Atomic single-document operations

yes

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

Roles, resources, and access types

yes

users and table-level permissions

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