DBMS > Dgraph vs. H2GIS vs. InfinityDB vs. RRDtool

System Properties Comparison Dgraph vs. H2GIS vs. InfinityDB vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Spatial extension of H2

A Java embedded Key-Value Store which extends the Java Map interface

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

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Website

dgraph.io

www.h2gis.org

boilerbay.com

oss.oetiker.ch/rrdtool

Technical documentation

dgraph.io/docs

www.h2gis.org/docs/home

boilerbay.com/infinitydb/manual

oss.oetiker.ch/rrdtool/doc

Developer

Dgraph Labs, Inc.

CNRS

Boiler Bay Inc.

Tobias Oetiker

Initial release

2016

2013

2002

1999

Current release

4.0

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

LGPL 3.0

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.

Implementation language

Java

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

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

HP-UX
Linux

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

in-process shared library
Pipes

Supported programming languages

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

Java

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

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

based on H2

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

none

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Concurrency

Support for concurrent manipulation of data

yes

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

Planned for future releases

yes

based on H2

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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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