DBMS > Amazon DynamoDB vs. Coveo vs. Heroic vs. openGauss

System Properties Comparison Amazon DynamoDB vs. Coveo vs. Heroic vs. openGauss

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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

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Primary database model

Document store
Key-value store

Search engine

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial 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	2.14
Rank	#116	Overall
	#11	Search engines

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	1.11
Rank	#175	Overall
	#79	Relational DBMS

Website

aws.amazon.com/dynamodb

www.coveo.com

github.com/spotify/heroic

gitee.com/opengauss
opengauss.org

Technical documentation

docs.aws.amazon.com/dynamodb

docs.coveo.com

spotify.github.io/heroic

docs.opengauss.org/en
gitee.com/opengauss/docs

Developer

Amazon

Coveo

Spotify

Huawei and openGauss community

Initial release

2012

2014

2019

Current release

3.0, March 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache 2.0

Open Source

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, C++, Java

Server operating systems

hosted

Linux

Data scheme

schema-free

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

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

via Elasticsearch

yes

SQL

Support of SQL

ANSI SQL 2011

APIs and other access methods

RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
Java
JavaScript
Python

C
C++
Java

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

yes

Sharding

horizontal partitioning (by range, list and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

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)

granular access controls, API key management, content filters

Access rights for users, groups and roles according to SQL-standard

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