DBMS > Amazon Redshift vs. Dragonfly vs. LokiJS vs. Microsoft Access vs. Oracle NoSQL

System Properties Comparison Amazon Redshift vs. Dragonfly vs. LokiJS vs. Microsoft Access vs. Oracle NoSQL

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Document store
Key-value store
Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

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

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

aws.amazon.com/redshift

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

github.com/techfort/LokiJS

www.microsoft.com/en-us/microsoft-365/access

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

docs.aws.amazon.com/redshift

www.dragonflydb.io/docs

techfort.github.io/LokiJS

developer.microsoft.com/en-us/access

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Amazon (based on PostgreSQL)

DragonflyDB team and community contributors

Microsoft

Oracle

Initial release

2012

2023

2014

1992

2011

Current release

1.0, March 2023

1902 (16.0.11328.20222), March 2019

23.3, December 2023

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

Open Source

commercial

Bundled with Microsoft Office

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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++

Java

Server operating systems

hosted

Linux

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

Windows

Not a real database server, but making use of DLLs

Linux
Solaris SPARC/x86

Data scheme

yes

scheme-free

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

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

yes

optional

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

but not compliant to any SQL standard

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protocol

JavaScript API

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

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
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

View functions in JavaScript

yes

since Access 2010 using the ACE-engine

Triggers

publish/subscribe channels provide some trigger functionality

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

atomic operations within a single collection possible

ACID

but no files for transaction logging

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

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

but no files for transaction logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

Password-based authentication

a simple user-level security was built in till version Access 2003

Access rights for users and roles

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