DBMS > Hazelcast vs. InterSystems Caché vs. Transbase vs. Yanza

System Properties Comparison Hazelcast vs. InterSystems Caché vs. Transbase vs. Yanza

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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.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A widely adopted in-memory data grid

A multi-model DBMS and application server

A resource-optimized, high-performance, universally applicable RDBMS

Time Series DBMS for IoT Applications

Primary database model

Key-value store

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

hazelcast.com

www.intersystems.com/products/cache

www.transaction.de/en/products/transbase.html

yanza.com

Technical documentation

hazelcast.org/imdg/docs

docs.intersystems.com

www.transaction.de/en/products/transbase/features.html

Developer

Hazelcast

InterSystems

Transaction Software GmbH

Yanza

Initial release

2008

1997

1987

2015

Current release

5.3.6, November 2023

2018.1.4, May 2020

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

free development license

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM

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

FreeBSD
Linux
macOS
Solaris
Windows

Windows

Data scheme

schema-free

depending on used data model

yes

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C#
C++
Java

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

Triggers

yes

Events

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Role-based access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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