DBMS > Amazon Redshift vs. IBM Db2 Event Store vs. Oracle vs. Quasardb

System Properties Comparison Amazon Redshift vs. IBM Db2 Event Store vs. Oracle vs. Quasardb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Distributed Event Store optimized for Internet of Things use cases

Widely used RDBMS

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

Time Series DBMS

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	17.94
Rank	#34	Overall
	#21	Relational DBMS

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

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

aws.amazon.com/redshift

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

www.oracle.com/database

quasar.ai

Technical documentation

docs.aws.amazon.com/redshift

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

docs.oracle.com/en/database

doc.quasar.ai/master

Developer

Amazon (based on PostgreSQL)

IBM

Oracle

quasardb

Initial release

2012

2017

1980

2009

Current release

2.0

23c, September 2023

3.14.1, January 2024

License

Commercial or Open Source

commercial

free developer edition available

commercial

restricted free version is available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

C++

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

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

BSD
Linux
OS X
Windows

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

restricted

yes

with tags

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

through the embedded Spark runtime

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-active shard replication

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

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

yes

by using LevelDB

In-memory capabilities

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

yes

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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.