DBMS > IBM Db2 Event Store vs. InterSystems Caché vs. RDF4J vs. RocksDB vs. Yaacomo

System Properties Comparison IBM Db2 Event Store vs. InterSystems Caché vs. RDF4J vs. RocksDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Distributed Event Store optimized for Internet of Things use cases

A multi-model DBMS and application server

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Event Store
Time Series DBMS

Key-value store
Object oriented DBMS
Relational DBMS

RDF store

Key-value store

Relational DBMS

Secondary database models

Document store

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

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

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

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

www.intersystems.com/products/cache

rdf4j.org

rocksdb.org

yaacomo.com

Technical documentation

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

docs.intersystems.com

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

Developer

IBM

InterSystems

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Facebook, Inc.

Q2WEB GmbH

Initial release

2017

1997

2004

2013

2009

Current release

2.0

2018.1.4, May 2020

8.11.4, April 2024

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

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++

Java

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Linux

Android
Linux
Windows

Data scheme

yes

depending on used data model

yes

RDF Schemas

schema-free

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

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

C++ API
Java API

JDBC
ODBC

Supported programming languages

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

C#
C++
Java

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Source-replica replication

none

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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 support depends on the API used

yes

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 storage is supported as well

yes

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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