DBMS > ClickHouse vs. GridGain vs. JaguarDB vs. Oracle Rdb vs. RRDtool

System Properties Comparison ClickHouse vs. GridGain vs. JaguarDB vs. Oracle Rdb vs. RRDtool

Editorial information provided by DB-Engines

Name

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.

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

Performant, highly scalable DBMS for AI and IoT applications

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

Relational DBMS

Key-value store
Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

clickhouse.com

www.gridgain.com

www.jaguardb.com

www.oracle.com/database/technologies/related/rdb.html

oss.oetiker.ch/rrdtool

Technical documentation

clickhouse.com/docs

www.gridgain.com/docs/index.html

www.jaguardb.com/support.html

www.oracle.com/database/technologies/related/rdb-doc.html

oss.oetiker.ch/rrdtool/doc

Developer

Clickhouse Inc.

GridGain Systems, Inc.

DataJaguar, Inc.

Oracle, originally developed by Digital Equipment Corporation (DEC)

Tobias Oetiker

Initial release

2016

2007

2015

1984

1999

Current release

v24.4.1.2088-stable, May 2024

GridGain 8.5.1

3.3 July 2023

7.4.1.1, 2021

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL V3.0

commercial

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

C++

Java, C++, .Net

C++

the server part. Clients available in other languages

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

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Solaris
Windows

Linux

HP Open VMS

HP-UX
Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

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.

yes

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

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

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

JDBC
ODBC

in-process shared library
Pipes

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

yes

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

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

none

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)

Multi-source replication

none

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

Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

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

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.

Security Hooks for custom implementations

rights management via user accounts

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