DBMS > Amazon Redshift vs. AnzoGraph DB vs. NSDb vs. OpenQM vs. RethinkDB

System Properties Comparison Amazon Redshift vs. AnzoGraph DB vs. NSDb vs. OpenQM vs. RethinkDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#10	Multivalue DBMS

Score	2.84
Rank	#106	Overall
	#19	Document stores

Website

aws.amazon.com/redshift

cambridgesemantics.com/anzograph

nsdb.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

rethinkdb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

nsdb.io/Architecture

rethinkdb.com/docs

Developer

Amazon (based on PostgreSQL)

Cambridge Semantics

Rocket Software, originally Martin Phillips

The Linux Foundation

since July 2017

Initial release

2012

2018

2017

1993

2009

Current release

2.3, January 2021

3.4-12

2.4.1, August 2020

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

GPLv2, extended commercial license available

Open Source

Apache Version 2

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

Linux
macOS

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

Schema-free and OWL/RDFS-schema support

yes

with some exceptions

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.

yes

Secondary indexes

restricted

all fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like query language

APIs and other access methods

JDBC
ODBC

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

gRPC
HTTP REST
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
Python

Java
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions and aggregates

yes

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

yes

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in MPP-Cluster

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

not needed in graphs

Transaction concepts

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

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

Access rights for users and roles

Access rights can be defined down to the item level

yes

users and table-level permissions

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