DBMS > Amazon DocumentDB vs. GBase vs. Ignite vs. RDF4J

System Properties Comparison Amazon DocumentDB vs. GBase vs. Ignite vs. RDF4J

Please select another system to include it in the comparison.

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.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store

Relational DBMS

Key-value store
Relational DBMS

RDF store

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	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

aws.amazon.com/documentdb

www.gbase.cn

ignite.apache.org

rdf4j.org

Technical documentation

aws.amazon.com/documentdb/resources

apacheignite.readme.io/docs

rdf4j.org/documentation

Developer

General Data Technology Co., Ltd.

Apache Software Foundation

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2019

2004

2015

2004

Current release

GBase 8a, GBase 8s, GBase 8c

Apache Ignite 2.6

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C, Java, Python

C++, Java, .Net

Java

Server operating systems

hosted

Linux

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

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

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
C API
JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C#
C++
Java
PHP
Python
Ruby
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

yes

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

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

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

Security Hooks for custom implementations

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

AWS announces vector search for Amazon DocumentDB
29 November 2023, AWS Blog

Use headless clusters in Amazon DocumentDB for cost-effective multi-Region resiliency | Amazon Web Services
8 March 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0 | Amazon Web Services
15 April 2024, AWS Blog

Game Developer's Guide to Amazon DocumentDB (with MongoDB compatibility) Part Three: Operation Best Practices ...
25 January 2024, AWS Blog

provided by Google News

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

Apache Ignite: An Overview
6 September 2023, Open Source For You

GridGain Releases Conference Schedule for Virtual Apache Ignite Summit 2023
1 June 2023, Datanami

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

provided by Google News

Share this page