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DBMS > Cachelot.io vs. EsgynDB vs. Heroic vs. RDF4J vs. SQL.JS

System Properties Comparison Cachelot.io vs. EsgynDB vs. Heroic vs. RDF4J vs. SQL.JS

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

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.

Port of SQLite to JavaScript

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Website

github.com/spotify/heroic

Technical documentation

spotify.github.io/heroic

rdf4j.org/documentation

sql.js.org/documentation/index.html

Developer

Esgyn

Spotify

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

Alon Zakai

enhancements implemented by others

Initial release

2015

2015

2014

2004

2012

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Cloud-based only

Only available as a cloud service

no

no

no

no

no

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C++, Java

Java

Java

JavaScript

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux
OS X
Unix
Windows

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

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

no

yes

yes

yes

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.

no

no

no

no

Secondary indexes

no

yes

yes

via Elasticsearch

yes

SQL

Support of SQL

no

yes

no

no

yes

SQL-92 is not fully supported

APIs and other access methods

Memcached protocol

ADO.NET
JDBC
ODBC

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

JavaScript API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

Java
PHP
Python

JavaScript

Server-side scripts

Stored procedures

no

Java Stored Procedures

no

yes

no

Triggers

no

no

no

yes

no

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding

none

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

yes

none

none

MapReduce

Offers an API for user-defined Map/Reduce methods

no

yes

no

no

no

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

no

yes

no

yes

Transaction concepts

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

no

ACID

no

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes

yes

yes

Durability

Support for making data persistent

no

yes

yes

yes

in-memory storage is supported as well

no

except by serializing a db to a file

In-memory capabilities

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

no

no

no

yes

User concepts

Access control

no

fine grained access rights according to SQL-standard

no

no

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More resources

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