DBMS > Dgraph vs. Drizzle vs. RRDtool vs. ToroDB

System Properties Comparison Dgraph vs. Drizzle vs. RRDtool vs. ToroDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed and scalable native Graph DBMS

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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.

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

dgraph.io

oss.oetiker.ch/rrdtool

github.com/torodb/server

Technical documentation

dgraph.io/docs

oss.oetiker.ch/rrdtool/doc

Developer

Dgraph Labs, Inc.

Drizzle project, originally started by Brian Aker

Tobias Oetiker

8Kdata

Initial release

2016

2008

1999

2016

Current release

7.2.4, September 2012

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

Open Source

GPL V2 and FLOSS

Open Source

AGPL-V3

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

C++

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

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

HP-UX
Linux

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes

string, integer, double, boolean, date, object_id

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

with proprietary extensions

APIs and other access methods

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

JDBC

in-process shared library
Pipes

Supported programming languages

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

C
C++
Java
PHP

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

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication
Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

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

by using the rrdcached daemon

yes

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

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

show all

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