DBMS > gStore vs. LeanXcale vs. Sadas Engine vs. Valentina Server

System Properties Comparison gStore vs. LeanXcale vs. Sadas Engine vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

A native Graph DBMS to store and maintain very large RDF datasets.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

Object-relational database and reports server

Primary database model

Graph DBMS
RDF store

Key-value store
Relational DBMS

Relational DBMS

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

Score	0.03
Rank	#367	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Website

Technical documentation

en.gstore.cn/#/enDocs

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

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

LeanXcale

SADAS s.r.l.

Paradigma Software

Initial release

2016

2015

2006

1999

Current release

1.2, November 2023

8.0

5.7.5

License

Commercial or Open Source

Open Source

BSD

commercial

free trial version available

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

Linux

AIX
Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free and OWL/RDFS-schema support

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

yes

SQL

Support of SQL

yes

through Apache Derby

yes

APIs and other access methods

HTTP API
SPARQL 1.1

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC
Proprietary protocol

ODBC

Supported programming languages

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

C
Java
Scala

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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

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

Transaction concepts

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

yes

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.

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

Users, roles and permissions, Role-Based Access Control (RBAC) supported

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

fine grained access rights according to SQL-standard

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More resources

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