DBMS > IBM Db2 Event Store vs. MaxDB vs. NSDb vs. Oracle Coherence

System Properties Comparison IBM Db2 Event Store vs. MaxDB vs. NSDb vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

A robust and reliable RDBMS optimized to run all major SAP solutions

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Oracles in-memory data grid solution

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Time Series DBMS

Key-value store

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

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

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

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

maxdb.sap.com

nsdb.io

www.oracle.com/java/coherence

Technical documentation

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

maxdb.sap.com/documentation

nsdb.io/Architecture

docs.oracle.com/en/middleware/standalone/coherence

Developer

IBM

SAP, acquired from Software AG (Adabas-D) in 1997

Oracle

Initial release

2017

1984

2017

2007

Current release

2.0

7.9.10.12, February 2024

14.1, August 2023

License

Commercial or Open Source

commercial

free developer edition available

commercial

Limited community edition free

Open Source

Apache Version 2.0

commercial

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, Scala

Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS

All OS with a Java VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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.

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

SQL-like query language

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
WebDAV

gRPC
HTTP REST
WebSocket

JCache
JPA
RESTful HTTP API

Supported programming languages

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

.Net
C#
Java
Perl
PHP
Python

Java
Scala

.Net
C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

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

Using Apache Lucene

yes

optionally

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

authentification to access the cache via certificates or http basic authentication

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