DBMS > Amazon Neptune vs. Atos Standard Common Repository vs. BaseX vs. ObjectBox vs. SiriDB

System Properties Comparison Amazon Neptune vs. Atos Standard Common Repository vs. BaseX vs. ObjectBox vs. SiriDB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Fast, reliable graph database built for the cloud

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Open Source Time Series DBMS

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Native XML DBMS

Object oriented DBMS
Vector DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

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

Score	2.20
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	1.56
Rank	#141	Overall
	#4	Native XML DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

aws.amazon.com/neptune

atos.net/en/convergence-creators/portfolio/standard-common-repository

basex.org

github.com/objectbox
objectbox.io

siridb.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.basex.org

docs.objectbox.io

docs.siridb.com

Developer

Amazon

Atos Convergence Creators

BaseX GmbH

ObjectBox Limited

Cesbit

Initial release

2017

2016

2007

2017

Current release

1703

11.2, August 2024

4.0 (May 2024)

License

Commercial or Open Source

commercial

Open Source

BSD license

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

MIT License

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

Java

C and C++

Server operating systems

hosted

Linux

Linux
OS X
Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux

Data scheme

schema-free

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

XQuery supports types

yes, plus "flex" map-like types

yes

Numeric data

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

yes

SQL

Support of SQL

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

LDAP

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Proprietary native API

HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

All languages with LDAP bindings

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

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

Server-side scripts

Stored procedures

yes

Triggers

yes

via events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

none

Sharding

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.

yes

none

Data sync between devices allowing occasional connected databases to work completely offline

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

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

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

LDAP bind authentication

Users with fine-grained authorization concept on 4 levels

yes

simple rights management via user accounts

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

How Apollo Tyres built their tyre genealogy solution using Amazon Neptune and Amazon Bedrock
25 September 2024, AWS Blog

How Amazon stores deliver trustworthy shopping and seller experiences using Amazon Neptune
18 September 2024, AWS Blog

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13 September 2024, AWS Blog

Amazon Neptune Analytics now supports openCypher queries over RDF Graphs
13 August 2024, AWS Blog

New Amazon Neptune engine version delivers up to 9 times faster and 10 times higher throughput for openCypher query performance
23 July 2024, AWS Blog

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