DBMS > Drizzle vs. Heroic vs. Prometheus vs. Stardog vs. Valentina Server

System Properties Comparison Drizzle vs. Heroic vs. Prometheus vs. Stardog vs. Valentina Server

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

Open-source Time Series DBMS and monitoring system

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Object-relational database and reports server

Primary database model

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

github.com/spotify/heroic

prometheus.io

www.stardog.com

www.valentina-db.net

Technical documentation

spotify.github.io/heroic

prometheus.io/docs

docs.stardog.com

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Drizzle project, originally started by Brian Aker

Spotify

Stardog-Union

Paradigma Software

Initial release

2008

2014

2015

2010

1999

Current release

7.2.4, September 2012

7.3.0, May 2020

5.7.5

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Import/export of XML data possible

Secondary indexes

yes

via Elasticsearch

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

with proprietary extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

APIs and other access methods

JDBC

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

RESTful HTTP/JSON API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ODBC

Supported programming languages

C
C++
Java
PHP

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

hooks for callbacks inside the server can be used.

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

by Federation

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

none

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

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

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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