DBMS > 4D vs. Apache Jena - TDB vs. GigaSpaces vs. MongoDB vs. RRDtool

System Properties Comparison 4D vs. Apache Jena - TDB vs. GigaSpaces vs. MongoDB vs. RRDtool

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Relational DBMS

RDF store

Document store
Object oriented DBMS

Values are user defined objects

Document store

Time Series DBMS

Secondary database models

Graph DBMS
Search engine

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	2.68
Rank	#110	Overall
	#54	Relational DBMS

Score	3.85
Rank	#86	Overall
	#3	RDF stores

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	423.96
Rank	#5	Overall
	#1	Document stores

Score	2.14
Rank	#124	Overall
	#10	Time Series DBMS

Website

www.4d.com

jena.apache.org/documentation/tdb/index.html

www.gigaspaces.com

www.mongodb.com

oss.oetiker.ch/rrdtool

Technical documentation

developer.4d.com

jena.apache.org/documentation/tdb/index.html

docs.gigaspaces.com/latest/landing.html

www.mongodb.com/docs/manual

oss.oetiker.ch/rrdtool/doc

Developer

4D, Inc

Apache Software Foundation

originally developed by HP Labs

Gigaspaces Technologies

MongoDB, Inc

Tobias Oetiker

Initial release

1984

2000

2009

1999

Current release

v20, April 2023

4.9.0, July 2023

15.5, September 2020

6.0.7, June 2023

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

Apache License, Version 2.0

Open Source

Apache Version 2; Commercial licenses available

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

Java

Java, C++, .Net

C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

OS X
Windows

All OS with a Java VM

Linux
macOS
Solaris
Windows

Linux
OS X
Solaris
Windows

HP-UX
Linux

Data scheme

yes

RDF Schemas

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

Numeric data only

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

XML can be used for describing objects metadata

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-99 for query and DML statements

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

in-process shared library
Pipes

Supported programming languages

4D proprietary IDE
PHP

Java

.Net
C++
Java
Python
Scala

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

via event handler

yes, event driven architecture

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

none

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

TDB Transactions

ACID

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

Durability

Support for making data persistent

yes

optional, enabled by default

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

Users and groups

Access control via Jena Security

Role-based access control

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more

Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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.