DBMS > IBM Db2 Event Store vs. Microsoft SQL Server vs. OpenQM vs. searchxml vs. Stardog

System Properties Comparison IBM Db2 Event Store vs. Microsoft SQL Server vs. OpenQM vs. searchxml vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Microsofts flagship relational DBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

DBMS for structured and unstructured content wrapped with an application server

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

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Multivalue DBMS

Native XML DBMS
Search engine

Graph DBMS
RDF store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

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

www.microsoft.com/en-us/sql-server

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

www.searchxml.net/category/products

www.stardog.com

Technical documentation

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

learn.microsoft.com/en-US/sql/sql-server

www.searchxml.net/support/handouts

docs.stardog.com

Developer

IBM

Microsoft

Rocket Software, originally Martin Phillips

informationpartners gmbh

Stardog-Union

Initial release

2017

1989

1993

2015

2010

Current release

2.0

SQL Server 2022, November 2022

3.4-12

1.0

7.3.0, May 2020

License

Commercial or Open Source

commercial

free developer edition available

commercial

restricted free version is available

Open Source

GPLv2, extended commercial license available

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

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Implementation language

C and C++

C++

Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Windows

Linux
macOS
Windows

Data scheme

yes

with some exceptions

schema-free

schema-free and OWL/RDFS-schema support

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

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

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API
WebDAV
XQuery
XSLT

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

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

.Net
Basic
C
Java
Objective C
PHP
Python

C++

most other programming languages supported via APIs

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

on the application server

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes, but depending on the SQL-Server Edition

yes

sychronisation to multiple collections

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

Eventual Consistency

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

multiple readers, single writer

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

Access rights can be defined down to the item level

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

Access rights for users and roles

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