DBMS > ReductStore vs. Riak KV vs. SAP Adaptive Server vs. Trafodion

System Properties Comparison ReductStore vs. Riak KV vs. SAP Adaptive Server vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Distributed, fault tolerant key-value store

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

Transactional SQL-on-Hadoop DBMS

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

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	32.67
Rank	#25	Overall
	#17	Relational DBMS

Website

github.com/reductstore
www.reduct.store

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

trafodion.apache.org

Technical documentation

www.reduct.store/docs

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

help.sap.com/docs/SAP_ASE

trafodion.apache.org/documentation.html

Developer

ReductStore LLC

OpenSource, formerly Basho Technologies

SAP, Sybase

Apache Software Foundation, originally developed by HP

Initial release

2023

2009

1987

2014

Current release

1.9, March 2024

3.2.0, December 2022

16.0

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Business Source License 1.1

Open Source

Apache version 2, commercial enterprise edition

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Rust

Erlang

C and C++

C++, Java

Server operating systems

Docker
Linux
macOS
Windows

Linux
OS X

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux

Data scheme

schema-free

yes

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

APIs and other access methods

HTTP API

HTTP API
Native Erlang Interface

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

ADO.NET
JDBC
ODBC

Supported programming languages

C++
JavaScript (Node.js)
Python
Rust

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Erlang

Java and Transact-SQL

Java Stored Procedures

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

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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