DBMS > DataFS vs. HugeGraph vs. Microsoft SQL Server vs. OpenEdge vs. RavenDB

System Properties Comparison DataFS vs. HugeGraph vs. Microsoft SQL Server vs. OpenEdge vs. RavenDB

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

A fast-speed and highly-scalable Graph DBMS

Microsofts flagship relational DBMS

Application development environment with integrated database management system

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Secondary database models

Graph DBMS

Document store
Graph DBMS
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

newdatabase.com

github.com/hugegraph
hugegraph.apache.org

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

www.progress.com/openedge

ravendb.net

Technical documentation

dev.mobiland.com/Overview.xsp

hugegraph.apache.org/docs

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

documentation.progress.com/output/ua/OpenEdge_latest

ravendb.net/docs

Developer

Mobiland AG

Baidu

Microsoft

Progress Software Corporation

Hibernating Rhinos

Initial release

2018

1989

1984

2010

Current release

1.1.263, October 2022

0.9

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

Open Source

AGPL version 3, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Windows

Linux
macOS
Unix

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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.

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language (RQL)

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

Java API
RESTful HTTP API
TinkerPop Gremlin

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

JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
VB.Net

Groovy
Java
Python

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

Progress proprietary ABL (Advanced Business Language)

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

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

yes

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

yes

depending on used storage backend, e.g. Cassandra and HBase

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

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes, but depending on the SQL-Server Edition

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

User concepts

Access control

Windows-Profile

Users, roles and permissions

fine grained access rights according to SQL-standard

Users and groups

Authorization levels configured per client per database

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