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

System Properties Comparison Amazon DocumentDB vs. GBase vs. JanusGraph vs. Kingbase 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

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store
Spatial DBMS

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	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

aws.amazon.com/documentdb

www.gbase.cn

janusgraph.org

www.kingbase.com.cn

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

BeiJing KINGBASE Information technologies inc.

Oracle, TimesTen Performance Software, HP

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

Initial release

2019

2004

2017

1999

1998

Current release

GBase 8a, GBase 8s, GBase 8c

0.6.3, February 2023

V8.0, August 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

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

C, Java, Python

Java

C and Java

Server operating systems

hosted

Linux

Linux
OS X
Unix
Windows

Linux
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

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

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Clojure
Java
Python

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

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)

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

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

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

Immediate Consistency

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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