DBMS > Amazon CloudSearch vs. Amazon DynamoDB vs. Microsoft Access vs. Solr vs. TinkerGraph

System Properties Comparison Amazon CloudSearch vs. Amazon DynamoDB vs. Microsoft Access vs. Solr vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

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

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 widely used distributed, scalable search engine based on Apache Lucene

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Search engine

Document store
Key-value store

Relational DBMS

Search engine

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

aws.amazon.com/cloudsearch

aws.amazon.com/dynamodb

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

solr.apache.org

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.aws.amazon.com/dynamodb

developer.microsoft.com/en-us/access

solr.apache.org/resources.html

Developer

Amazon

Microsoft

Apache Software Foundation

Initial release

2012

1992

2006

2009

Current release

1902 (16.0.11328.20222), March 2019

9.6.0, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Bundled with Microsoft Office

Open Source

Apache Version 2

Open Source

Apache 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.

Implementation language

C++

Java

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

all search fields are automatically indexed

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

but not compliant to any SQL standard

Solr Parallel SQL Interface

APIs and other access methods

HTTP API

RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

Java API
RESTful HTTP/JSON API

TinkerPop 3

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Groovy
Java

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

Java plugins

Triggers

yes

by integration with AWS Lambda

yes

since Access 2010 using the ACE-engine

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

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

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

authentication via encrypted signatures

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

yes

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