DBMS > IBM Db2 Event Store vs. InfinityDB vs. Microsoft SQL Server vs. Oracle vs. SAP HANA

System Properties Comparison IBM Db2 Event Store vs. InfinityDB vs. Microsoft SQL Server vs. Oracle vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

A Java embedded Key-Value Store which extends the Java Map interface

Microsofts flagship relational DBMS

Widely used RDBMS

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Event Store
Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.07
Rank	#359	Overall
	#54	Key-value stores

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Website

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

boilerbay.com

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

www.oracle.com/database

www.sap.com/products/hana.html

Technical documentation

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

boilerbay.com/infinitydb/manual

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

docs.oracle.com/en/database

help.sap.com/hana

Developer

IBM

Boiler Bay Inc.

Microsoft

Oracle

SAP

Initial release

2017

2002

1989

1980

2010

Current release

2.0

4.0

SQL Server 2022, November 2022

23c, September 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free developer edition available

commercial

restricted free version is available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based 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

C++

C and C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

All OS with a Java VM

Linux
Windows

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

Appliance or cloud-service

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

with proprietary extensions

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

Supported programming languages

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

Java

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

Server-side scripts

Stored procedures

yes

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

PL/SQL

also stored procedures in Java possible

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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