DBMS > Amazon DocumentDB vs. GBase vs. JanusGraph vs. mSQL vs. TimesTen

System Properties Comparison Amazon DocumentDB vs. GBase vs. JanusGraph vs. mSQL vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A Graph DBMS optimized for distributed clusters

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

In-Memory RDBMS compatible to Oracle

Primary database model

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

aws.amazon.com/documentdb

www.gbase.cn

janusgraph.org

hughestech.com.au/products/msql

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

Technical documentation

aws.amazon.com/documentdb/resources

docs.janusgraph.org

docs.oracle.com/database/timesten-18.1

Developer

General Data Technology Co., Ltd.

Linux Foundation; originally developed as Titan by Aurelius

Hughes Technologies

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2019

2004

2017

1994

1998

Current release

GBase 8a, GBase 8s, GBase 8c

0.6.3, February 2023

4.4, October 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free licenses can be provided

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

C, Java, Python

Java

Server operating systems

hosted

Linux

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
C API
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Clojure
Java
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

none

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Relationships in graphs

yes

Transaction concepts

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

Atomic single-document operations

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

by means of logfiles and checkpoints

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

yes

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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