DBMS > Sadas Engine vs. Tkrzw vs. Ultipa

System Properties Comparison Sadas Engine vs. Tkrzw vs. Ultipa

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Editorial information provided by DB-Engines

Name

Description

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Relational DBMS

Key-value store

Graph DBMS

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

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

www.sadasengine.com

dbmx.net/tkrzw

www.ultipa.com

Technical documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.ultipa.com/document

Developer

SADAS s.r.l.

Mikio Hirabayashi

Ultipa

Initial release

2006

2020

2019

Current release

8.0

0.9.3, August 2020

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

commercial

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++

Server operating systems

AIX
Linux
Windows

Linux
macOS

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

APIs and other access methods

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++
Java
Python
Ruby

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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.

yes

managed by 'Learn by Usage'

yes

using specific database classes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

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