DBMS > IBM Db2 Event Store vs. InterSystems Caché vs. JanusGraph vs. SQLite

System Properties Comparison IBM Db2 Event Store vs. InterSystems Caché vs. JanusGraph vs. SQLite

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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.

Description

Distributed Event Store optimized for Internet of Things use cases

A multi-model DBMS and application server

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Widely used embeddable, in-process RDBMS

Primary database model

Event Store
Time Series DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store

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

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

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

www.intersystems.com/products/cache

janusgraph.org

www.sqlite.org

Technical documentation

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

docs.intersystems.com

docs.janusgraph.org

www.sqlite.org/docs.html

Developer

IBM

InterSystems

Linux Foundation; originally developed as Titan by Aurelius

Dwayne Richard Hipp

Initial release

2017

1997

2017

2000

Current release

2.0

2018.1.4, May 2020

1.0.0, October 2023

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

Apache 2.0

Open Source

Public Domain

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++

Java

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

server-less

Data scheme

yes

depending on used data model

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Clojure
Java
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

via file-system locks

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

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