DBMS > 4D vs. IBM Db2 Event Store vs. RDFox vs. SAP HANA

System Properties Comparison 4D vs. IBM Db2 Event Store vs. RDFox vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Distributed Event Store optimized for Internet of Things use cases

High performance knowledge graph and semantic reasoning engine

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

www.4d.com

www.ibm.com/products/db2-event-store

www.oxfordsemantic.tech

www.sap.com/products/hana.html

Technical documentation

developer.4d.com

www.ibm.com/docs/en/db2-event-store

docs.oxfordsemantic.tech

help.sap.com/hana

Developer

4D, Inc

IBM

Oxford Semantic Technologies

SAP

Initial release

1984

2017

2010

Current release

v20, April 2023

2.0

6.0, Septermber 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free developer edition available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

C++

Server operating systems

OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
macOS
Windows

Appliance or cloud-service

Data scheme

yes

RDF schemas

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

yes

close to SQL 92

yes

through the embedded Spark runtime

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API
SPARQL 1.1

JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C
Java

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Active-active shard replication

replication via a shared file system

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

fine grained access rights according to SQL-standard

Roles, resources, and access types

yes

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