DBMS > Dragonfly vs. EsgynDB vs. Riak KV vs. SiteWhere vs. Yanza

System Properties Comparison Dragonfly vs. EsgynDB vs. Riak KV vs. SiteWhere vs. Yanza

Editorial information provided by DB-Engines

Name

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

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Distributed, fault tolerant key-value store

M2M integration platform for persisting/querying time series data

Time Series DBMS for IoT Applications

Primary database model

Key-value store

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Time Series DBMS

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

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

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

www.esgyn.cn

github.com/sitewhere/sitewhere

yanza.com

Technical documentation

www.dragonflydb.io/docs

www.tiot.jp/riak-docs/riak/kv/latest

sitewhere1.sitewhere.io/index.html

Developer

DragonflyDB team and community contributors

Esgyn

OpenSource, formerly Basho Technologies

SiteWhere

Yanza

Initial release

2023

2015

2009

2010

2015

Current release

1.0, March 2023

3.2.0, December 2022

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

Common Public Attribution License Version 1.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C++, Java

Erlang

Java

Server operating systems

Linux

Linux
OS X

Linux
OS X
Windows

Windows

Data scheme

scheme-free

yes

schema-free

predefined scheme

schema-free

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

restricted

SQL

Support of SQL

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

HTTP REST

HTTP API

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

All languages supporting JDBC/ODBC/ADO.Net

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

any language that supports HTTP calls

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

Erlang

Triggers

publish/subscribe channels provide some trigger functionality

yes

pre-commit hooks and post-commit hooks

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication between multi datacenters

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

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

yes, using Riak Security

Users with fine-grained authorization concept

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More resources

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