DBMS > Amazon DynamoDB vs. Apache Doris vs. Coveo vs. EsgynDB

System Properties Comparison Amazon DynamoDB vs. Apache Doris vs. Coveo vs. EsgynDB

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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

An MPP-based analytics DBMS embracing the MySQL protocol

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Primary database model

Document store
Key-value store

Relational DBMS

Search engine

Relational DBMS

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.61
Rank	#235	Overall
	#110	Relational DBMS

Score	2.14
Rank	#116	Overall
	#11	Search engines

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Website

aws.amazon.com/dynamodb

doris.apache.org
github.com/apache/doris

www.coveo.com

www.esgyn.cn

Technical documentation

docs.aws.amazon.com/dynamodb

github.com/apache/doris/wiki

docs.coveo.com

Developer

Amazon

Apache Software Foundation, originally contributed from Baidu

Coveo

Esgyn

Initial release

2012

2017

2012

2015

Current release

1.2.2, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 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

Java

C++, Java

Server operating systems

hosted

Linux

hosted

Linux

Data scheme

schema-free

yes

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

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

APIs and other access methods

RESTful HTTP API

JDBC
MySQL client

RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java

C#
Java
JavaScript
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

Multi-source replication between multi datacenters

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

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

yes

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.

User concepts

Access control

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

fine grained access rights according to SQL-standard

granular access controls, API key management, content filters

fine grained access rights according to SQL-standard

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