DBMS > H2GIS vs. Kyligence Enterprise vs. ObjectBox vs. RRDtool

System Properties Comparison H2GIS vs. Kyligence Enterprise vs. ObjectBox vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

A distributed analytics engine for big data, built on top of Apache Kylin

Extremely fast embedded database for small devices, IoT and Mobile

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

Secondary database models

Relational DBMS

Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

www.h2gis.org

kyligence.io/kyligence-enterprise

objectbox.io

oss.oetiker.ch/rrdtool

Technical documentation

www.h2gis.org/docs/home

docs.objectbox.io

oss.oetiker.ch/rrdtool/doc

Developer

CNRS

Kyligence, Inc.

ObjectBox Limited

Tobias Oetiker

Initial release

2013

2016

2017

1999

Current release

1.8.0, 2022

License

Commercial or Open Source

Open Source

LGPL 3.0

commercial

Open Source

Apache License 2.0

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.

Implementation language

Java

C and C++

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

Server operating systems

Linux

Android
iOS
Linux
macOS
Windows

HP-UX
Linux

Data scheme

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary native API

in-process shared library
Pipes

Supported programming languages

Java

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

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

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

online/offline synchronization between client and server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

yes

based on H2

yes

More information provided by the system vendor

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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