DBMS > ClickHouse vs. GeoSpock vs. GridGain vs. RDF4J vs. Tibero

System Properties Comparison ClickHouse vs. GeoSpock vs. GridGain vs. RDF4J vs. Tibero

Editorial information provided by DB-Engines

Name

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

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Spatial and temporal data processing engine for extreme data scale

GridGain is an in-memory computing platform, built on Apache Ignite

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

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

Key-value store
Relational DBMS

RDF store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

clickhouse.com

geospock.com

www.gridgain.com

rdf4j.org

us.tmaxsoft.com/products/tibero

Technical documentation

clickhouse.com/docs

www.gridgain.com/docs/index.html

rdf4j.org/documentation

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Clickhouse Inc.

GeoSpock

GridGain Systems, Inc.

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

TmaxSoft

Initial release

2016

2007

2004

2003

Current release

v24.4.1.2088-stable, May 2024

2.0, September 2019

GridGain 8.5.1

6, April 2015

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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.

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Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

Java, Javascript

Java, C++, .Net

Java

C and Assembler

Server operating systems

FreeBSD
Linux
macOS

hosted

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

RDF Schemas

yes

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.

yes

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

ANSI SQL for query only (using Presto)

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C#
C++
Java
PHP
Python
Ruby
Scala

Java
PHP
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

yes (compute grid and cache interceptors can be used instead)

yes

Persistent Stored Procedure (PSM)

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Automatic sharding

Sharding

none

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes (replicated cache)

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

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.

yes

planned for next version

User concepts

Access control

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Access rights for users can be defined per table

Security Hooks for custom implementations

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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