DBMS > IBM Db2 Event Store vs. Impala vs. Oracle vs. SAP Adaptive Server

System Properties Comparison IBM Db2 Event Store vs. Impala vs. Oracle vs. SAP Adaptive Server

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Analytic DBMS for Hadoop

Widely used RDBMS

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph

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

Score	0.41
Rank	#243	Overall
	#2	Event Stores
	#17	Time Series DBMS

Score	15.36
Rank	#38	Overall
	#23	Relational DBMS

Score	1322.93
Rank	#1	Overall
	#1	Relational DBMS

Score	54.61
Rank	#18	Overall
	#12	Relational DBMS

Website

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

www.cloudera.com/products/open-source/apache-hadoop/impala.html

www.oracle.com/database

www.sap.com/products/sybase-ase.html

Technical documentation

www.ibm.com/support/knowledgecenter/en/SSGNPV_2.0.0/welcome.html

docs.cloudera.com/documentation/enterprise/latest/topics/impala.html

docs.oracle.com/en/database

help.sap.com/viewer/product/SAP_ASE

Developer

IBM

Cloudera

Oracle

SAP, Sybase

Initial release

2017

2013

1980

1987

Current release

2.0

3.3.0, August 2019

19c, February 2019

16.0

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache Version 2

commercial

restricted free version is available

commercial

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++

C++

C and C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux

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

AIX
HP-UX
Linux
Solaris
Unix
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

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

Supported programming languages

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

All languages supporting JDBC/ODBC

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++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PL/SQL

also stored procedures in Java possible

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

with the optional Oracle Partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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