DBMS > Bangdb vs. Dragonfly vs. InfluxDB vs. Linter vs. MySQL

System Properties Comparison Bangdb vs. Dragonfly vs. InfluxDB vs. Linter vs. MySQL

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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

DBMS for storing time series, events and metrics

RDBMS for high security requirements

Widely used open source RDBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

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

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

bangdb.com

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

www.influxdata.com/products/influxdb-overview

linter.ru

www.mysql.com

Technical documentation

docs.bangdb.com

www.dragonflydb.io/docs

docs.influxdata.com/influxdb

dev.mysql.com/doc

Developer

Sachin Sinha, BangDB

DragonflyDB team and community contributors

relex.ru

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2012

2023

2013

1990

1995

Current release

BangDB 2.0, October 2021

1.0, March 2023

2.7.6, April 2024

8.4.0, April 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

BSL 1.1

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are 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.

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Implementation language

C, C++

C++

C and C++

Server operating systems

Linux

Linux
OS X

through Homebrew

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

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

scheme-free

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

Numeric data and Strings

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

HTTP API
JSON over UDP

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

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Java
Python

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

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

proprietary syntax

Triggers

yes, Notifications (with Streaming only)

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

in enterprise version only

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

selectable replication factor

in enterprise version only

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes, strict serializability by the server

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

Depending on used storage engine

yes

User concepts

Access control

yes (enterprise version only)

Password-based authentication

simple rights management via user accounts

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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