DBMS > Datomic vs. IBM Db2 Event Store vs. Oracle vs. SAP IQ

System Properties Comparison Datomic vs. IBM Db2 Event Store vs. Oracle vs. SAP IQ

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Distributed Event Store optimized for Internet of Things use cases

Widely used RDBMS

Columnar RDBMS optimized for Big Data analytics

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

column-oriented

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

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

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Website

www.datomic.com

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

www.oracle.com/database

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

docs.datomic.com

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

docs.oracle.com/en/database

help.sap.com/docs/SAP_IQ

Developer

Cognitect

IBM

Oracle

SAP, formerly Sybase

Initial release

2012

2017

1980

1994

Current release

1.0.7075, December 2023

2.0

23c, September 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

limited edition free

commercial

free developer edition available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C and C++

Server operating systems

All OS with a Java VM

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Schemaless in JSON and XML columns

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

through the embedded Spark runtime

yes

with proprietary extensions

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Clojure
Java

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

PL/SQL

also stored procedures in Java possible

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Sharding, horizontal partitioning

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Active-active shard replication

Multi-source replication
Source-replica replication

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

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