DBMS > Amazon Neptune vs. ObjectBox

System Properties Comparison Amazon Neptune vs. ObjectBox

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Our visitors often compare Amazon Neptune and ObjectBox with MongoDB, RocksDB and Google Cloud Firestore.

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

Primary database model

Graph DBMS
RDF store

Object oriented DBMS
Vector DBMS

Secondary database models

Time Series DBMS

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

Score	2.13
Rank	#111	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	1.11
Rank	#175	Overall
	#7	Object oriented DBMS
	#13	Vector DBMS

Website

aws.amazon.com/neptune

github.com/objectbox
objectbox.io

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.objectbox.io

Developer

Amazon

ObjectBox Limited

Initial release

2017

Current release

4.0 (May 2024)

License

Commercial or Open Source

commercial

Bindings are released under Apache 2.0

Apache License 2.0

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 and C++

Server operating systems

hosted

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

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

yes

SQL

Support of SQL

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Proprietary native API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

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.

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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.

User concepts

Access control

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

yes

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