DBMS > Ehcache vs. HyperSQL vs. TimesTen vs. Yanza

System Properties Comparison Ehcache vs. HyperSQL vs. TimesTen vs. Yanza

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Editorial information provided by DB-Engines

Name

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

Description

A widely adopted Java cache with tiered storage options

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Time Series DBMS for IoT Applications

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

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

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.ehcache.org

hsqldb.org

www.oracle.com/database/technologies/related/timesten.html

yanza.com

Technical documentation

www.ehcache.org/documentation

hsqldb.org/web/hsqlDocsFrame.html

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Terracotta Inc, owned by Software AG

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Yanza

Initial release

2009

2001

1998

2015

Current release

3.10.0, March 2022

2.7.2, June 2023

Release 22.1

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

based on BSD 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

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Windows

Data scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JCache

HTTP API

JDBC via HTTP
JDBC
ODBC

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

HTTP API

Supported programming languages

Java

All languages supporting JDBC/ODBC
Java

C
C++
Java
Node.js
PL/SQL
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

Java, SQL

PL/SQL

Triggers

yes

Cache Event Listeners

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

by means of logfiles and checkpoints

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

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