DBMS > Apache Jena - TDB vs. EsgynDB vs. HugeGraph vs. Lovefield

System Properties Comparison Apache Jena - TDB vs. EsgynDB vs. HugeGraph vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A fast-speed and highly-scalable Graph DBMS

Embeddable relational database for web apps written in pure JavaScript

Primary database model

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

jena.apache.org/documentation/tdb/index.html

www.esgyn.cn

github.com/hugegraph
hugegraph.apache.org

google.github.io/lovefield

Technical documentation

jena.apache.org/documentation/tdb/index.html

hugegraph.apache.org/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Apache Software Foundation

originally developed by HP Labs

Esgyn

Baidu

Google

Initial release

2000

2015

2018

2014

Current release

4.9.0, July 2023

0.9

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

C++, Java

Java

JavaScript

Server operating systems

All OS with a Java VM

Linux

Linux
macOS
Unix

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

RDF Schemas

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

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

ADO.NET
JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

Java

All languages supporting JDBC/ODBC/ADO.Net

Groovy
Java
Python

JavaScript

Server-side scripts

Stored procedures

yes

Java Stored Procedures

asynchronous Gremlin script jobs

Triggers

yes

via event handler

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

TDB Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Access control via Jena Security

fine grained access rights according to SQL-standard

Users, roles and permissions

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