DBMS > HugeGraph vs. OpenMLDB vs. Sadas Engine

System Properties Comparison HugeGraph vs. OpenMLDB vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

An open-source machine learning database that provides a feature platform for training and inference

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

Primary database model

Graph DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

openmldb.ai

www.sadasengine.com

Technical documentation

hugegraph.apache.org/docs

openmldb.ai/docs/zh/main

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

Developer

Baidu

4 Paradigm Inc.

SADAS s.r.l.

Initial release

2018

2020

2006

Current release

0.9

2024-2 February 2024

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

free trial version 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++, Java, Scala

C++

Server operating systems

Linux
macOS
Unix

Linux

AIX
Linux
Windows

Data scheme

yes

Fixed schema

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

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
SQLAlchemy

JDBC
ODBC
Proprietary protocol

Supported programming languages

Groovy
Java
Python

C++
Go
Java
Python
Scala

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

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual 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

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'

User concepts

Access control

Users, roles and permissions

fine grained access rights according to SQL-standard

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

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More resources

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