DBMS > DataFS vs. HugeGraph vs. LevelDB vs. Percona Server for MongoDB vs. Sadas Engine

System Properties Comparison DataFS vs. HugeGraph vs. LevelDB vs. Percona Server for MongoDB vs. Sadas Engine

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Primary database model

Secondary database models

Graph DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

newdatabase.com

github.com/hugegraph
hugegraph.apache.org

github.com/google/leveldb

www.percona.com/mongodb/software/percona-server-for-mongodb

www.sadasengine.com

Technical documentation

dev.mobiland.com/Overview.xsp

hugegraph.apache.org/docs

github.com/google/leveldb/blob/main/doc/index.md

docs.percona.com/percona-distribution-for-mongodb

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

Developer

Mobiland AG

Baidu

Google

Percona

SADAS s.r.l.

Initial release

2018

2011

2015

2006

Current release

1.1.263, October 2022

0.9

1.23, February 2021

3.4.10-2.10, November 2017

8.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

GPL Version 2

commercial

free trial version available

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

Java

C++

Server operating systems

Windows

Linux
macOS
Unix

Illumos
Linux
OS X
Windows

Linux

AIX
Linux
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

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

Java API
RESTful HTTP API
TinkerPop Gremlin

proprietary protocol using JSON

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
C
C#
C++
VB.Net

Groovy
Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

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

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

JavaScript

Triggers

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

yes

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

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

none

Source-replica replication

none

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

with automatic compression on writes

yes

In-memory capabilities

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

yes

via In-Memory Engine

yes

managed by 'Learn by Usage'

User concepts

Access control

Windows-Profile

Users, roles and permissions

Access rights for users and roles

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

More information provided by the system vendor

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