DBMS > Drizzle vs. Heroic vs. RDFox vs. SQream DB

System Properties Comparison Drizzle vs. Heroic vs. RDFox vs. SQream DB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

High performance knowledge graph and semantic reasoning engine

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.22
Rank	#305	Overall
	#25	Graph DBMS
	#15	RDF stores

Score	0.62
Rank	#234	Overall
	#109	Relational DBMS

Website

github.com/spotify/heroic

www.oxfordsemantic.tech

sqream.com

Technical documentation

spotify.github.io/heroic

docs.oxfordsemantic.tech

docs.sqream.com

Developer

Drizzle project, originally started by Brian Aker

Spotify

Oxford Semantic Technologies

SQream Technologies

Initial release

2008

2014

2017

Current release

7.2.4, September 2012

6.0, Septermber 2022

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

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

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

FreeBSD
Linux
OS X

Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

yes

RDF schemas

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

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

RESTful HTTP API
SPARQL 1.1

.Net
JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

C
Java

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions in Python

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

replication via a shared file system

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Roles, resources, and access types

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More resources

DB-Engines blog posts

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