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

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

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Editorial information provided by DB-Engines

Name

Description

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

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

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

Primary database model

Key-value store

Document store
Key-value store
Relational DBMS

Document store
Object oriented DBMS

RDF store

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

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

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	0.69
Rank	#230	Overall
	#9	RDF stores

Website

github.com/google/leveldb

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

origodb.com

rdf4j.org

Technical documentation

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

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

origodb.com/docs

rdf4j.org/documentation

Developer

Google

Oracle

Robert Friberg et al

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

Initial release

2011

2009

under the name LiveDB

2004

Current release

1.23, February 2021

23.3, December 2023

License

Commercial or Open Source

Open Source

BSD

Open Source

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

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

Server operating systems

Illumos
Linux
OS X
Windows

Linux
Solaris SPARC/x86

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

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

yes

RDF Schemas

Typing

predefined data types such as float or date

optional

User defined using .NET types and collections

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

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

.NET Client API
HTTP API
LINQ

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Source-replica 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

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

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

with automatic compression on writes

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

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