DBMS > Apache Druid vs. GeoSpock vs. RDF4J vs. Yanza

System Properties Comparison Apache Druid vs. GeoSpock vs. RDF4J vs. Yanza

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Editorial information provided by DB-Engines

Name

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

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

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Spatial and temporal data processing engine for extreme data scale

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

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

RDF store

Time Series DBMS

Secondary database models

Time Series DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

druid.apache.org

geospock.com

rdf4j.org

yanza.com

Technical documentation

druid.apache.org/docs/latest/design

rdf4j.org/documentation

Developer

Apache Software Foundation and contributors

GeoSpock

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

Yanza

Initial release

2012

2004

2015

Current release

30.0.0, June 2024

2.0, September 2019

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, Javascript

Java

Server operating systems

Linux
OS X
Unix

hosted

Linux
OS X
Unix
Windows

Windows

Data scheme

yes

schema-less columns are supported

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

SQL for querying

ANSI SQL for query only (using Presto)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users can be defined per table

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More resources

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