DBMS > Amazon SimpleDB vs. BaseX vs. Cassandra vs. Microsoft Access vs. Milvus

System Properties Comparison Amazon SimpleDB vs. BaseX vs. Cassandra vs. Microsoft Access vs. Milvus

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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 DBMS designed for efficient storage of vector data and vector similarity searches

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	1.88
Rank	#139	Overall
	#24	Key-value stores

Score	1.90
Rank	#136	Overall
	#4	Native XML DBMS

Score	103.86
Rank	#12	Overall
	#1	Wide column stores

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	1.81
Rank	#144	Overall
	#5	Vector DBMS

Website

aws.amazon.com/simpledb

basex.org

cassandra.apache.org

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

milvus.io

Technical documentation

docs.aws.amazon.com/simpledb

docs.basex.org

cassandra.apache.org/doc/latest

developer.microsoft.com/en-us/access

milvus.io/docs/overview.md

Developer

Amazon

BaseX GmbH

Apache Software Foundation

Apache top level project, originally developped by Facebook

Microsoft

Initial release

2007

2008

1992

2019

Current release

10.7, August 2023

4.1.3, July 2023

1902 (16.0.11328.20222), March 2019

2.3.4, January 2024

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

Apache version 2

commercial

Bundled with Microsoft Office

Open Source

Apache Version 2.0

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Java

C++

C++, Go

Server operating systems

hosted

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

yes

Vector, Numeric and String

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

All columns are indexed automatically

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

yes

but not compliant to any SQL standard

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

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

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

Triggers

yes

via events

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Sharding

no "single point of failure"

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

Representation of geographical distribution of servers is possible

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

multiple readers, single writer

Atomicity and isolation are supported for single operations

ACID

but no files for transaction logging

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.

yes

User concepts

Access control

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

Users with fine-grained authorization concept on 4 levels

Access rights for users can be defined per object

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

Role based access control and fine grained access rights

More information provided by the system vendor

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