DBMS > Amazon Redshift vs. LokiJS vs. Microsoft Azure Cosmos DB vs. PlanetScale vs. Sadas Engine

System Properties Comparison Amazon Redshift vs. LokiJS vs. Microsoft Azure Cosmos DB vs. PlanetScale vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

In-memory JavaScript DBMS

Globally distributed, horizontally scalable, multi-model database service

Scalable, distributed, serverless MySQL database platform built on top of Vitess

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

aws.amazon.com/redshift

github.com/techfort/LokiJS

azure.microsoft.com/services/cosmos-db

planetscale.com

www.sadasengine.com

Technical documentation

docs.aws.amazon.com/redshift

techfort.github.io/LokiJS

learn.microsoft.com/azure/cosmos-db

planetscale.com/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Amazon (based on PostgreSQL)

Microsoft

PlanetScale

SADAS s.r.l.

Initial release

2012

2014

2020

2006

Current release

8.0

License

Commercial or Open Source

commercial

Open Source

commercial

free trial 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

JavaScript

C++

Server operating systems

hosted

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

hosted

Docker
Linux
macOS

AIX
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

restricted

yes

via views

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

JavaScript API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
MySQL protocol
ODBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

JavaScript

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

View functions in JavaScript

JavaScript

yes

proprietary syntax

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

Multi-item ACID transactions with snapshot isolation within a partition

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

Access rights for users, groups and roles according to SQL-standard

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