DBMS > 4D vs. InfinityDB vs. jBASE vs. SiteWhere vs. Stardog

System Properties Comparison 4D vs. InfinityDB vs. jBASE vs. SiteWhere vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A Java embedded Key-Value Store which extends the Java Map interface

A robust multi-value DBMS comprising development tools and middleware

M2M integration platform for persisting/querying time series data

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.4d.com

boilerbay.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

github.com/sitewhere/sitewhere

www.stardog.com

Technical documentation

developer.4d.com

boilerbay.com/infinitydb/manual

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

sitewhere1.sitewhere.io/index.html

docs.stardog.com

Developer

4D, Inc

Boiler Bay Inc.

Rocket Software (formerly Zumasys)

SiteWhere

Stardog-Union

Initial release

1984

2002

1991

2010

Current release

v20, April 2023

4.0

5.7

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

OS X
Windows

All OS with a Java VM

AIX
Linux
Windows

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

predefined scheme

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

optional

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

Import/export of XML data possible

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

close to SQL 92

Embedded SQL for jBASE in BASIC

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

HTTP REST

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

4D proprietary IDE
PHP

Java

.Net
Basic
Jabbascript
Java

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes

selectable replication factor

based on HBase

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

relationships in graphs

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Users and groups

Access rights can be defined down to the item level

Users with fine-grained authorization concept

Access rights for users and roles

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
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