DBMS > Riak TS vs. SAP Adaptive Server vs. Transbase vs. VictoriaMetrics vs. Yanza

System Properties Comparison Riak TS vs. SAP Adaptive Server vs. Transbase vs. VictoriaMetrics vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

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

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Time Series DBMS for IoT Applications

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

www.sap.com/products/technology-platform/sybase-ase.html

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

victoriametrics.com

yanza.com

Technical documentation

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

help.sap.com/docs/SAP_ASE

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

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Open Source, formerly Basho Technologies

SAP, Sybase

Transaction Software GmbH

VictoriaMetrics

Yanza

Initial release

2015

1987

2018

2015

Current release

3.0.0, September 2022

16.0

Transbase 8.3, 2022

v1.91, May 2023

License

Commercial or Open Source

Open Source

commercial

free development license

Open Source

Apache Version 2.0

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

Erlang

C and C++

Server operating systems

Linux
OS X

AIX
HP-UX
Linux
Solaris
Unix
Windows

FreeBSD
Linux
macOS
Solaris
Windows

FreeBSD
Linux
macOS
OpenBSD

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

restricted

yes

SQL

Support of SQL

yes, limited

yes

APIs and other access methods

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC
Proprietary native API

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

HTTP API

Supported programming languages

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
Java
Perl
PHP
Python

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

Erlang

Java and Transact-SQL

yes

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

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication

Synchronous 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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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