DBMS > GeoSpock vs. IRONdb vs. MySQL vs. RDF4J vs. Rockset

System Properties Comparison GeoSpock vs. IRONdb vs. MySQL vs. RDF4J vs. Rockset

Editorial information provided by DB-Engines

Name

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

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Spatial and temporal data processing engine for extreme data scale

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Widely used open source RDBMS

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

RDF store

Document store

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

Relational DBMS
Search engine

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

geospock.com

www.circonus.com/solutions/time-series-database/

www.mysql.com

rdf4j.org

rockset.com

Technical documentation

docs.circonus.com/irondb/category/getting-started

dev.mysql.com/doc

rdf4j.org/documentation

docs.rockset.com

Developer

GeoSpock

Circonus LLC.

Oracle

since 2010, originally MySQL AB, then Sun

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

Rockset

Initial release

2017

1995

2004

2019

Current release

2.0, September 2019

V0.10.20, January 2018

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java, Javascript

C and C++

Java

C++

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

hosted

Data scheme

yes

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

dynamic typing

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.

yes

ingestion from XML files supported

Secondary indexes

temporal, categorical

yes

all fields are automatically indexed

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

with proprietary extensions

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
PHP
Python

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes, in Lua

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Automatic, metric affinity per node

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

Access rights for users can be defined per table

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and organizations can be defined via Rockset console

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