DBMS > Ehcache vs. Lovefield vs. OceanBase vs. RDF4J vs. TerminusDB

System Properties Comparison Ehcache vs. Lovefield vs. OceanBase vs. RDF4J vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Embeddable relational database for web apps written in pure JavaScript

A distributed, high available RDBMS compatible with Oracle and MySQL

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Document store
Wide column store

Document store
RDF store

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

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	1.97
Rank	#119	Overall
	#58	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

www.ehcache.org

google.github.io/lovefield

en.oceanbase.com

rdf4j.org

terminusdb.com

Technical documentation

www.ehcache.org/documentation

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

en.oceanbase.com/docs/oceanbase-database

rdf4j.org/documentation

terminusdb.github.io/terminusdb/#

Developer

Terracotta Inc, owned by Software AG

Google

OceanBase

previously Alibaba and Ant Group

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

DataChemist Ltd.

Initial release

2009

2014

2010

2004

2018

Current release

3.10.0, March 2022

2.1.12, February 2017

4.3.0, April 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

Commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPL V3

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

JavaScript

C++

Java

Prolog, Rust

Server operating systems

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

Linux

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

SQL-like query language (WOQL)

APIs and other access methods

JCache

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Java

JavaScript

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Java
PHP
Python

JavaScript
Python

Server-side scripts

Stored procedures

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

yes

Triggers

yes

Cache Event Listeners

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

none

Multi-source replication using Paxos

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

yes

in-memory storage is supported as well

yes

in-memory journaling

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 rights for users, groups and roles according to SQL-standard

Role-based access control

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