DBMS > Amazon DynamoDB vs. Elasticsearch vs. KeyDB vs. Microsoft Access

System Properties Comparison Amazon DynamoDB vs. Elasticsearch vs. KeyDB vs. Microsoft Access

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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 distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

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.)

Primary database model

Document store
Key-value store

Search engine

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Website

aws.amazon.com/dynamodb

www.elastic.co/elasticsearch

github.com/Snapchat/KeyDB
keydb.dev

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

Technical documentation

docs.aws.amazon.com/dynamodb

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.keydb.dev

developer.microsoft.com/en-us/access

Developer

Amazon

Elastic

EQ Alpha Technology Ltd.

Microsoft

Initial release

2012

2010

2019

1992

Current release

8.6, January 2023

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Elastic License

Open Source

BSD-3

commercial

Bundled with Microsoft Office

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++

Server operating systems

hosted

All OS with a Java VM

Linux

Windows

Not a real database server, but making use of DLLs

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

All search fields are automatically indexed

yes

by using the Redis Search module

yes

SQL

Support of SQL

SQL-like query language

yes

but not compliant to any SQL standard

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP/JSON API

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

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

Server-side scripts

Stored procedures

yes

Lua

yes

since Access 2010 using the ACE-engine

Triggers

yes

by integration with AWS Lambda

yes

by using the 'percolation' feature

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency
Strong eventual consistency with CRDTs

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

but no files for transaction logging

In-memory capabilities

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

Memcached and Redis integration

yes

User concepts

Access control

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

simple password-based access control and ACL

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

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