DBMS > IBM Db2 Event Store vs. RDF4J vs. SAP Advantage Database Server vs. SiteWhere

System Properties Comparison IBM Db2 Event Store vs. RDF4J vs. SAP Advantage Database Server vs. SiteWhere

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed Event Store optimized for Internet of Things use cases

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

Low-cost RDBMS with access to ISAM and FoxPro data structures

M2M integration platform for persisting/querying time series data

Primary database model

Event Store
Time Series DBMS

RDF store

Relational DBMS

Time Series DBMS

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

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Website

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

rdf4j.org

www.sap.com/products/advantage-database-server.html

github.com/sitewhere/sitewhere

Technical documentation

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

rdf4j.org/documentation

sitewhere1.sitewhere.io/index.html

Developer

IBM

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

Sybase, SAP

SiteWhere

Initial release

2017

2004

1993

2010

Current release

2.0

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

Common Public Attribution License Version 1.0

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

C and C++

Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Unix
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

yes

predefined scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

HTTP REST

Supported programming languages

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

Java
PHP
Python

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

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

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

yes

caching of (temporary) tables can be configured

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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

Mudhakar Srivatsa
11 December 2023, IBM Research

Best cloud databases of 2022
4 October 2022, ITPro

Why a robust data management strategy is essential today | IBM HDM
19 September 2019, Express Computer

How IBM Is Turning Db2 into an ‘AI Database’
3 June 2019, Datanami

provided by Google News

SAP Patch Day: August 2024
4 September 2024, all-about-security.de

Critical Updates Released on August 2024 SAP Security Patch Day
27 August 2024, InsideSAP

SAP Announces Q3 2023 Results: Asia Pacific and Japan View
19 October 2023, SAP News

provided by Google News

SiteWhere: An open platform for connected devices
11 July 2017, Open Source For You

Top Open-Source Tools for IoT Development in 2024
5 September 2024, Analytics Insight

11 Best Open source IoT Platforms To Develop Smart Projects
9 March 2023, H2S Media

provided by Google News

Share this page