DBMS > Amazon DynamoDB vs. Ehcache vs. Microsoft Access vs. Spark SQL

System Properties Comparison Amazon DynamoDB vs. Ehcache vs. Microsoft Access vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

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

A widely adopted Java cache with tiered storage options

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.)

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store
Key-value store

Key-value store

Relational 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	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

aws.amazon.com/dynamodb

www.ehcache.org

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

spark.apache.org/sql

Technical documentation

docs.aws.amazon.com/dynamodb

www.ehcache.org/documentation

developer.microsoft.com/en-us/access

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Amazon

Terracotta Inc, owned by Software AG

Microsoft

Apache Software Foundation

Initial release

2012

2009

1992

2014

Current release

3.10.0, March 2022

1902 (16.0.11328.20222), March 2019

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2; commercial licenses available

commercial

Bundled with Microsoft Office

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Scala

Server operating systems

hosted

All OS with a Java VM

Windows

Not a real database server, but making use of DLLs

Linux
OS X
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

JCache

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

Triggers

yes

by integration with AWS Lambda

yes

Cache Event Listeners

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Tunable Consistency (Strong, Eventual, Weak)

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

yes

supports JTA and can work as an XA resource

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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)

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

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