DBMS > JanusGraph vs. Microsoft SQL Server vs. OpenEdge vs. TDSQL for MySQL vs. Valentina Server

System Properties Comparison JanusGraph vs. Microsoft SQL Server vs. OpenEdge vs. TDSQL for MySQL vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Microsofts flagship relational DBMS

Application development environment with integrated database management system

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Object-relational database and reports server

Primary database model

Graph DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

janusgraph.org

www.microsoft.com/en-us/sql-server

www.progress.com/openedge

www.tencentcloud.com/products/dcdb

www.valentina-db.net

Technical documentation

docs.janusgraph.org

learn.microsoft.com/en-US/sql/sql-server

documentation.progress.com/output/ua/OpenEdge_latest

www.tencentcloud.com/document/product/1042

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

Developer

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Progress Software Corporation

Tencent

Paradigma Software

Initial release

2017

1989

1984

2013

1999

Current release

0.6.3, February 2023

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

hosted

Linux
OS X
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

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

JDBC
ODBC

ODBC

Supported programming languages

Clojure
Java
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Progress proprietary ABL (Advanced Business Language)

C
C#
C++
Java
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning

since Version 11.4

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

Users and groups

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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