DBMS > atoti vs. IBM Db2 Event Store vs. RDF4J vs. searchxml vs. SiteWhere

System Properties Comparison atoti vs. IBM Db2 Event Store vs. RDF4J vs. searchxml vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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.

DBMS for structured and unstructured content wrapped with an application server

M2M integration platform for persisting/querying time series data

Primary database model

Object oriented DBMS

Event Store
Time Series DBMS

RDF store

Native XML DBMS
Search engine

Time Series DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

atoti.io

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

rdf4j.org

www.searchxml.net/category/products

github.com/sitewhere/sitewhere

Technical documentation

docs.atoti.io

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

rdf4j.org/documentation

www.searchxml.net/support/handouts

sitewhere1.sitewhere.io/index.html

Developer

ActiveViam

IBM

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

informationpartners gmbh

SiteWhere

Initial release

2017

2004

2015

2010

Current release

2.0

1.0

License

Commercial or Open Source

commercial

free versions available

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

Java

C and C++

Java

C++

Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Unix
Windows

Windows

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

through the embedded Spark runtime

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

RESTful HTTP API
WebDAV
XQuery
XSLT

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Python

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

yes

sychronisation to multiple collections

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

Transaction concepts

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

ACID

Isolation support depends on the API used

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

Users with fine-grained authorization concept

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