DBMS > Amazon Neptune vs. JanusGraph vs. OpenEdge vs. Riak TS vs. SQLite

System Properties Comparison Amazon Neptune vs. JanusGraph vs. OpenEdge vs. Riak TS vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

A Graph DBMS optimized for distributed clusters

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

Application development environment with integrated database management system

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Widely used embeddable, in-process RDBMS

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	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/neptune

janusgraph.org

www.progress.com/openedge

www.sqlite.org

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.janusgraph.org

documentation.progress.com/output/ua/OpenEdge_latest

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

www.sqlite.org/docs.html

Developer

Amazon

Linux Foundation; originally developed as Titan by Aurelius

Progress Software Corporation

Open Source, formerly Basho Technologies

Dwayne Richard Hipp

Initial release

2017

1984

2015

2000

Current release

0.6.3, February 2023

OpenEdge 12.2, March 2020

3.0.0, September 2022

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

Server operating systems

hosted

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

restricted

yes

SQL

Support of SQL

yes

close to SQL 92

yes, limited

yes

SQL-92 is not fully supported

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

HTTP API
Native Erlang Interface

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Clojure
Java
Python

Progress proprietary ABL (Advanced Business Language)

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

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

horizontal partitioning

since Version 11.4

Sharding

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.

yes

Source-replica replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

yes

links between datasets can be stored

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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)

User authentification and security via Rexster Graph Server

Users and groups

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