DBMS > Amazon Aurora vs. JanusGraph vs. Machbase Neo vs. ObjectBox

System Properties Comparison Amazon Aurora vs. JanusGraph vs. Machbase Neo vs. ObjectBox

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Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

TimeSeries DBMS for AIoT and BigData

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

Primary database model

Relational DBMS

Graph DBMS

Time Series DBMS

Object oriented DBMS
Vector DBMS

Secondary database models

Document store

Time Series DBMS

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

Score	7.84
Rank	#44	Overall
	#28	Relational DBMS

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

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

Website

aws.amazon.com/rds/aurora

janusgraph.org

machbase.com

github.com/objectbox
objectbox.io

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

docs.janusgraph.org

machbase.com/dbms

docs.objectbox.io

Developer

Amazon

Linux Foundation; originally developed as Titan by Aurelius

Machbase

ObjectBox Limited

Initial release

2015

2017

2013

2017

Current release

1.0.0, October 2023

V8.0, August 2023

4.0 (May 2024)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free test version available

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

Java

C and C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Proprietary native API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Clojure
Java
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

yes

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

simple password-based access control

yes

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.

Related products and services

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

Recent citations in the news

Replace Amazon QLDB with Amazon Aurora PostgreSQL for audit use cases
18 July 2024, AWS Blog

Build generative AI applications with Amazon Aurora and Amazon Bedrock Knowledge Bases
2 February 2024, AWS Blog

Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda
14 May 2024, AWS Blog

Amazon Aurora MySQL version 2 (with MySQL 5.7 compatibility) to version 3 (with MySQL 8.0 compatibility) upgrade checklist, Part 1
18 March 2024, AWS Blog

How Infosys used Amazon Aurora zero-ETL integration with Amazon Redshift for near real-time analytics and insights
1 August 2024, AWS Blog

provided by Google News

Simple Deployment of a Graph Database: JanusGraph
12 October 2020, Towards Data Science

Database Deep Dives: JanusGraph
8 August 2019, IBM

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
3 October 2019, The New Stack

From graph db to graph embedding. In 7 simple steps. | by Andy Greatorex
30 July 2020, Towards Data Science

provided by Google News

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