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

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

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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.

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

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

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

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

RDF store

Secondary database models

Time Series DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

druid.apache.org

geospock.com

www.opengemini.org
github.com/openGemini

rdf4j.org

Technical documentation

druid.apache.org/docs/latest/design

docs.opengemini.org/guide

rdf4j.org/documentation

Developer

Apache Software Foundation and contributors

GeoSpock

Huawei and openGemini community

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

Initial release

2012

2022

2004

Current release

29.0.1, April 2024

2.0, September 2019

1.1, July 2023

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache Version 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

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
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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)

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC

HTTP REST

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Automatic sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

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

In-memory capabilities

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

yes

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

Administrators and common users accounts

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