DBMS > Dragonfly vs. IBM Cloudant vs. Machbase Neo

System Properties Comparison Dragonfly vs. IBM Cloudant vs. Machbase Neo

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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

Database as a Service offering based on Apache CouchDB

TimeSeries DBMS for AIoT and BigData

Primary database model

Key-value store

Document store

Time Series DBMS

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Website

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

www.ibm.com/products/cloudant

machbase.com

Technical documentation

www.dragonflydb.io/docs

cloud.ibm.com/docs/Cloudant

machbase.com/dbms

Developer

DragonflyDB team and community contributors

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Machbase

Initial release

2023

2010

2013

Current release

1.0, March 2023

V8.0, August 2023

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

free test version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Erlang

Server operating systems

Linux

hosted

Linux
macOS
Windows

Data scheme

scheme-free

schema-free

yes

Typing

predefined data types such as float or date

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

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP/JSON API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

Lua

View functions (Map-Reduce) in JavaScript

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of command blocks and scripts

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Optimistic 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

volatile and lookup table

User concepts

Access control

Password-based authentication

Access rights for users can be defined per database

simple password-based access control

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