DBMS > IBM Db2 Event Store vs. Ignite vs. RDFox vs. RocksDB

System Properties Comparison IBM Db2 Event Store vs. Ignite vs. RDFox vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

High performance knowledge graph and semantic reasoning engine

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

Primary database model

Event Store
Time Series DBMS

Key-value store
Relational DBMS

Graph DBMS
RDF store

Key-value store

Secondary database models

Relational DBMS

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	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

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

Website

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

ignite.apache.org

www.oxfordsemantic.tech

rocksdb.org

Technical documentation

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

apacheignite.readme.io/docs

docs.oxfordsemantic.tech

github.com/facebook/rocksdb/wiki

Developer

IBM

Apache Software Foundation

Oxford Semantic Technologies

Facebook, Inc.

Initial release

2017

2015

2017

2013

Current release

2.0

Apache Ignite 2.6

6.0, Septermber 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

commercial

Open Source

BSD

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, .Net

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux

Data scheme

yes

RDF schemas

schema-free

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

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

RESTful HTTP API
SPARQL 1.1

C++ API
Java API

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
PHP
Python
Ruby
Scala

C
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

yes (compute grid and cache interceptors can be used instead)

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes (replicated cache)

replication via a shared file system

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

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

User concepts

Access control

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

Roles, resources, and access types

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