DBMS > Cachelot.io vs. Ehcache vs. Heroic vs. RDF4J

System Properties Comparison Cachelot.io vs. Ehcache vs. Heroic vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

A widely adopted Java cache with tiered storage options

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Primary database model

Key-value store

Time Series DBMS

RDF store

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

cachelot.io

www.ehcache.org

github.com/spotify/heroic

rdf4j.org

Technical documentation

www.ehcache.org/documentation

spotify.github.io/heroic

rdf4j.org/documentation

Developer

Terracotta Inc, owned by Software AG

Spotify

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

Initial release

2015

2009

2014

2004

Current release

3.10.0, March 2022

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 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

C++

Java

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
OS X
Unix
Windows

Data scheme

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

via Elasticsearch

yes

SQL

Support of SQL

APIs and other access methods

Memcached protocol

JCache

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Java

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

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