DBMS > Drizzle vs. TimesTen vs. Yaacomo vs. Yanza

System Properties Comparison Drizzle vs. TimesTen vs. Yaacomo vs. Yanza

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

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

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

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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.

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

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Time Series DBMS

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

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

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

yaacomo.com

yanza.com

Technical documentation

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

Developer

Drizzle project, originally started by Brian Aker

Oracle

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

Q2WEB GmbH

Yanza

Initial release

2008

1998

2009

2015

Current release

7.2.4, September 2012

Release 22.1

License

Commercial or Open Source

Open Source

GNU GPL

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

C++

Server operating systems

FreeBSD
Linux
OS X

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

Android
Linux
Windows

Windows

Data scheme

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

with proprietary extensions

yes

APIs and other access methods

JDBC

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

JDBC
ODBC

HTTP API

Supported programming languages

C
C++
Java
PHP

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

PL/SQL

Triggers

hooks for callbacks inside the server can be used.

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica 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

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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More resources

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