DBMS > Altibase vs. HugeGraph vs. Qdrant vs. RDF4J

System Properties Comparison Altibase vs. HugeGraph vs. Qdrant vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

A fast-speed and highly-scalable Graph DBMS

A high-performance vector database with neural network or semantic-based matching

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

altibase.com

github.com/hugegraph
hugegraph.apache.org

github.com/qdrant/qdrant
qdrant.tech

rdf4j.org

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

hugegraph.apache.org/docs

qdrant.tech/documentation

rdf4j.org/documentation

Developer

Altibase

Baidu

Qdrant

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

1999

2018

2021

2004

Current release

v7.3, 2023, August 2023

0.9

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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++

Java

Rust

Java

Server operating systems

AIX
HP-UX
Linux

Linux
macOS
Unix

Docker
Linux
macOS
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

ANSI SQL-92

APIs and other access methods

JDBC
ODBC
Proprietary protocol

Java API
RESTful HTTP API
TinkerPop Gremlin

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C++
Java

Groovy
Java
Python

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Java
PHP
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

asynchronous Gremlin script jobs

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Collection-level 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

Immediate Consistency

Eventual Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users, roles and permissions

Key-based authentication

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