DBMS > Oracle NoSQL vs. OrigoDB vs. Qdrant vs. RDF4J

System Properties Comparison Oracle NoSQL vs. OrigoDB vs. Qdrant vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A fully ACID in-memory object graph database

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

Document store
Key-value store
Relational DBMS

Document store
Object oriented DBMS

Vector DBMS

RDF store

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

www.oracle.com/database/nosql/technologies/nosql

origodb.com

github.com/qdrant/qdrant
qdrant.tech

rdf4j.org

Technical documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

origodb.com/docs

qdrant.tech/documentation

rdf4j.org/documentation

Developer

Oracle

Robert Friberg et al

Qdrant

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

Initial release

2011

2009

under the name LiveDB

2021

2004

Current release

23.3, December 2023

License

Commercial or Open Source

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Java

Rust

Java

Server operating systems

Linux
Solaris SPARC/x86

Linux
Windows

Docker
Linux
macOS
Windows

Linux
OS X
Unix
Windows

Data scheme

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

optional

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

.NET Client API
HTTP API
LINQ

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#
Go
Java
JavaScript (Node.js)
Python

.Net

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

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

Collection-level replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

off heap cache

yes

User concepts

Access control

Access rights for users and roles

Role based authorization

Key-based authentication

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