DBMS > Dragonfly vs. LokiJS vs. Microsoft Azure AI Search vs. SiteWhere

System Properties Comparison Dragonfly vs. LokiJS vs. Microsoft Azure AI Search vs. SiteWhere

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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

In-memory JavaScript DBMS

Search-as-a-service for web and mobile app development

M2M integration platform for persisting/querying time series data

Primary database model

Secondary database models

Vector DBMS

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

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

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

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

github.com/techfort/LokiJS

azure.microsoft.com/en-us/services/search

github.com/sitewhere/sitewhere

Technical documentation

www.dragonflydb.io/docs

techfort.github.io/LokiJS

learn.microsoft.com/en-us/azure/search

sitewhere1.sitewhere.io/index.html

Developer

DragonflyDB team and community contributors

Microsoft

SiteWhere

Initial release

2023

2014

2015

2010

Current release

1.0, March 2023

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

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++

JavaScript

Java

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

hosted

Linux
OS X
Windows

Data scheme

scheme-free

schema-free

yes

predefined scheme

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

via views

yes

SQL

Support of SQL

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JavaScript API

RESTful HTTP API

HTTP REST

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

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

Lua

View functions in JavaScript

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate 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 single collection possible

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

yes

using Azure authentication

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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