DBMS > IBM Db2 Event Store vs. SiteWhere vs. Stardog vs. ToroDB

System Properties Comparison IBM Db2 Event Store vs. SiteWhere vs. Stardog vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed Event Store optimized for Internet of Things use cases

M2M integration platform for persisting/querying time series data

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Event Store
Time Series DBMS

Time Series DBMS

Graph DBMS
RDF store

Document store

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	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Website

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

github.com/sitewhere/sitewhere

www.stardog.com

github.com/torodb/server

Technical documentation

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

sitewhere1.sitewhere.io/index.html

docs.stardog.com

Developer

IBM

SiteWhere

Stardog-Union

8Kdata

Initial release

2017

2010

2016

Current release

2.0

7.3.0, May 2020

License

Commercial or Open Source

commercial

free developer edition available

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

Open Source

AGPL-V3

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
Windows

Linux
macOS
Windows

All OS with a Java 7 VM

Data scheme

yes

predefined scheme

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

through the embedded Spark runtime

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

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP 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

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

.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

Sharding

based on HBase

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

selectable replication factor

based on HBase

Multi-source replication in HA-Cluster

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency in HA-Cluster

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

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 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

Users with fine-grained authorization concept

Access rights for users and roles

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