DBMS > Amazon DynamoDB vs. Blueflood vs. EsgynDB vs. Microsoft Access vs. Microsoft Azure SQL Database

System Properties Comparison Amazon DynamoDB vs. Blueflood vs. EsgynDB vs. Microsoft Access vs. Microsoft Azure SQL Database

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Scalable TimeSeries DBMS based on Cassandra

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

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.)

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

Primary database model

Document store
Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Website

aws.amazon.com/dynamodb

blueflood.io

www.esgyn.cn

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

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

Technical documentation

docs.aws.amazon.com/dynamodb

github.com/rax-maas/blueflood/wiki

developer.microsoft.com/en-us/access

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

Developer

Amazon

Rackspace

Esgyn

Microsoft

Initial release

2012

2013

2015

1992

2010

Current release

1902 (16.0.11328.20222), March 2019

V12

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

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

Java

C++, Java

C++

Server operating systems

hosted

Linux
OS X

Linux

Windows

Not a real database server, but making use of DLLs

hosted

Data scheme

schema-free

predefined scheme

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

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

APIs and other access methods

RESTful HTTP API

HTTP REST

ADO.NET
JDBC
ODBC

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

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

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

since Access 2010 using the ACE-engine

Transact SQL

Triggers

yes

by integration with AWS Lambda

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Multi-source replication between multi datacenters

none

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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.

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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