DBMS > Drizzle vs. LeanXcale vs. LokiJS vs. Microsoft Azure SQL Database

System Properties Comparison Drizzle vs. LeanXcale vs. LokiJS vs. Microsoft Azure SQL Database

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

In-memory JavaScript DBMS

Database as a Service offering with high compatibility to Microsoft SQL Server

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Website

www.leanxcale.com

github.com/techfort/LokiJS

azure.microsoft.com/en-us/products/azure-sql/database

Technical documentation

techfort.github.io/LokiJS

docs.microsoft.com/en-us/azure/azure-sql

Developer

Drizzle project, originally started by Brian Aker

LeanXcale

Microsoft

Initial release

2008

2015

2014

2010

Current release

7.2.4, September 2012

V12

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

commercial

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

C++

Server operating systems

FreeBSD
Linux
OS X

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

hosted

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

through Apache Derby

yes

APIs and other access methods

JDBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JavaScript API

ADO.NET
JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

C
Java
Scala

JavaScript

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

View functions in JavaScript

Transact SQL

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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