DBMS > Dragonfly vs. Graphite vs. Linter vs. OpenQM

System Properties Comparison Dragonfly vs. Graphite vs. Linter vs. OpenQM

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Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

RDBMS for high security requirements

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

github.com/graphite-project/graphite-web

linter.ru

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

www.dragonflydb.io/docs

graphite.readthedocs.io

Developer

DragonflyDB team and community contributors

Chris Davis

relex.ru

Rocket Software, originally Martin Phillips

Initial release

2023

2006

1990

1993

Current release

1.0, March 2023

3.4-12

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license available

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++

Python

C and C++

Server operating systems

Linux

Linux
Unix

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

scheme-free

yes

with some exceptions

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

Numeric data only

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

SQL

Support of SQL

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

HTTP API
Sockets

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

JavaScript (Node.js)
Python

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

locking

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

Password-based authentication

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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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

show all

Recent citations in the news

DragonflyDB Announces $21m in New Funding and General Availability
21 March 2023, businesswire.com

DragonflyDB reels in $21M for its speedy in-memory database
21 March 2023, SiliconANGLE News

Dragonfly 1.0 Released For What Claims To Be The World's Fastest In-Memory Data Store
20 March 2023, Phoronix

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29 March 2023, Phoronix

SFU Computing Science researchers receive 2022 ACM SIGMOD Research Highlight Award.
24 February 2023, Simon Fraser University News

provided by Google News

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

The value of time series data and TSDBs
10 June 2021, InfoWorld

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

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