DBMS > Amazon DynamoDB vs. GeoMesa vs. Greenplum vs. Microsoft Azure AI Search

System Properties Comparison Amazon DynamoDB vs. GeoMesa vs. Greenplum vs. Microsoft Azure AI Search

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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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Search-as-a-service for web and mobile app development

Primary database model

Document store
Key-value store

Spatial DBMS

Relational DBMS

Search engine

Secondary database models

Document store
Spatial DBMS

Vector 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	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Website

aws.amazon.com/dynamodb

www.geomesa.org

greenplum.org

azure.microsoft.com/en-us/services/search

Technical documentation

docs.aws.amazon.com/dynamodb

www.geomesa.org/documentation/stable/user/index.html

docs.greenplum.org

learn.microsoft.com/en-us/azure/search

Developer

Amazon

CCRi and others

Pivotal Software Inc.

Microsoft

Initial release

2012

2014

2005

2015

Current release

5.0.0, May 2024

7.0.0, September 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache License 2.0

Open Source

Apache 2.0

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

Scala

Server operating systems

hosted

Linux

hosted

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.

yes

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
Java
Perl
Python
R

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

Source-replica replication

yes

Implicit feature of the cloud service

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

depending on storage layer

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

depending on storage layer

User concepts

Access control

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

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

yes

using Azure authentication

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