DBMS > Newts vs. Riak KV vs. Teradata vs. TimesTen vs. Yanza

System Properties Comparison Newts vs. Riak KV vs. Teradata vs. TimesTen vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

Time Series DBMS based on Cassandra

Distributed, fault tolerant key-value store

A hybrid cloud data analytics software platform (Teradata Vantage)

In-Memory RDBMS compatible to Oracle

Time Series DBMS for IoT Applications

Primary database model

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

opennms.github.io/newts

www.teradata.com

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

yanza.com

Technical documentation

github.com/OpenNMS/newts/wiki

www.tiot.jp/riak-docs/riak/kv/latest

docs.teradata.com

docs.oracle.com/database/timesten-18.1

Developer

OpenNMS Group

OpenSource, formerly Basho Technologies

Teradata

Oracle, TimesTen Performance Software, HP

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

Yanza

Initial release

2014

2009

1984

1998

2015

Current release

3.2.0, December 2022

Teradata Vantage 1.0 MU2, January 2019

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

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

Erlang

Server operating systems

Linux
OS X
Windows

Linux
OS X

hosted
Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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.

yes

Secondary indexes

restricted

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

SQL

Support of SQL

yes

SQL 2016 + extensions

yes

APIs and other access methods

HTTP REST
Java API

HTTP API
Native Erlang Interface

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP API

Supported programming languages

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

C
C++
Java
PL/SQL

any language that supports HTTP calls

Server-side scripts

Stored procedures

Erlang

yes

UDFs, stored procedures, table functions in parallel

PL/SQL

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

no "single point of failure"

Sharding

Hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

Multi-source replication
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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

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

yes, using Riak Security

fine grained access rights according to SQL-standard

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More resources

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