DBMS > Drizzle vs. Galaxybase vs. GeoSpock vs. RRDtool

System Properties Comparison Drizzle vs. Galaxybase vs. GeoSpock vs. RRDtool

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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.

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Scalable, ACID-compliant native distributed parallel graph platform

Spatial and temporal data processing engine for extreme data scale

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

galaxybase.com

geospock.com

oss.oetiker.ch/rrdtool

Technical documentation

oss.oetiker.ch/rrdtool/doc

Developer

Drizzle project, originally started by Brian Aker

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

GeoSpock

Tobias Oetiker

Initial release

2008

2017

1999

Current release

7.2.4, September 2012

Nov 20, November 2021

2.0, September 2019

1.8.0, 2022

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C and Java

Java, Javascript

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

FreeBSD
Linux
OS X

Linux

hosted

HP-UX
Linux

Data scheme

yes

Strong typed schema

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

temporal, categorical

SQL

Support of SQL

yes

with proprietary extensions

ANSI SQL for query only (using Presto)

APIs and other access methods

JDBC

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

JDBC

in-process shared library
Pipes

Supported programming languages

C
C++
Java
PHP

Go
Java
Python

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

user defined procedures and functions

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

Role-based access control

Access rights for users can be defined per table

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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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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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