DBMS > Amazon Neptune vs. Blueflood vs. Infobright vs. JanusGraph vs. Oracle Rdb

System Properties Comparison Amazon Neptune vs. Blueflood vs. Infobright vs. JanusGraph vs. Oracle Rdb

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Scalable TimeSeries DBMS based on Cassandra

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

A Graph DBMS optimized for distributed clusters

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

Primary database model

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	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

aws.amazon.com/neptune

blueflood.io

ignitetech.com/softwarelibrary/infobrightdb

janusgraph.org

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

aws.amazon.com/neptune/developer-resources

github.com/rax-maas/blueflood/wiki

docs.janusgraph.org

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Amazon

Rackspace

Ignite Technologies Inc.; formerly InfoBright Inc.

Linux Foundation; originally developed as Titan by Aurelius

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2017

2013

2005

2017

1984

Current release

0.6.3, February 2023

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Apache 2.0

commercial

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

Server operating systems

hosted

Linux
OS X

Linux
Windows

Linux
OS X
Unix
Windows

HP Open VMS

Data scheme

schema-free

predefined scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

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.

Secondary indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

HTTP REST

ADO.NET
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

yes

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

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.

selectable replication factor

based on Cassandra

Source-replica replication

yes

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

User authentification and security via Rexster Graph Server

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