DBMS > Galaxybase vs. LeanXcale vs. LevelDB vs. RDF4J

System Properties Comparison Galaxybase vs. LeanXcale vs. LevelDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

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

Primary database model

Graph DBMS

Key-value store
Relational DBMS

Key-value store

RDF store

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

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

galaxybase.com

www.leanxcale.com

github.com/google/leveldb

rdf4j.org

Technical documentation

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

rdf4j.org/documentation

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

LeanXcale

Google

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

Initial release

2017

2015

2011

2004

Current release

Nov 20, November 2021

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

BSD

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

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Implementation language

C and Java

C++

Java

Server operating systems

Linux

Illumos
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

Strong typed schema

yes

schema-free

yes

RDF Schemas

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

SQL

Support of SQL

yes

through Apache Derby

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Go
Java
Python

C
Java
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
PHP
Python

Server-side scripts

Stored procedures

user defined procedures and functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

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

with automatic compression on writes

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

Role-based access control

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