DBMS > Amazon Neptune vs. Quasardb vs. Riak KV vs. SiteWhere vs. Stardog

System Properties Comparison Amazon Neptune vs. Quasardb vs. Riak KV vs. SiteWhere vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Distributed, high-performance timeseries database

Distributed, fault tolerant key-value store

M2M integration platform for persisting/querying time series data

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Time Series DBMS

Graph DBMS
RDF store

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

aws.amazon.com/neptune

quasar.ai

github.com/sitewhere/sitewhere

www.stardog.com

Technical documentation

aws.amazon.com/neptune/developer-resources

doc.quasar.ai/master

www.tiot.jp/riak-docs/riak/kv/latest

sitewhere1.sitewhere.io/index.html

docs.stardog.com

Developer

Amazon

quasardb

OpenSource, formerly Basho Technologies

SiteWhere

Stardog-Union

Initial release

2017

2009

2010

Current release

3.14.1, January 2024

3.2.0, December 2022

7.3.0, May 2020

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache version 2, commercial enterprise edition

Open Source

Common Public Attribution License Version 1.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

Erlang

Java

Server operating systems

hosted

BSD
Linux
OS X
Windows

Linux
OS X

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

schema-free

predefined scheme

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

integer and binary

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.

Import/export of XML data possible

Secondary indexes

yes

with tags

restricted

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

HTTP API

HTTP API
Native Erlang Interface

HTTP REST

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

Erlang

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

pre-commit hooks and post-commit hooks

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

consistent hashing

Sharding

no "single point of failure"

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Source-replica replication with selectable replication factor

selectable replication factor

based on HBase

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

Relationships in graphs

links between data sets can be stored

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Cryptographically strong user authentication and audit trail

yes, using Riak Security

Users with fine-grained authorization concept

Access rights for users and roles

More information provided by the system vendor

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