DBMS > Amazon DynamoDB vs. Hyprcubd vs. Microsoft Azure Cosmos DB vs. Yanza vs. YottaDB

System Properties Comparison Amazon DynamoDB vs. Hyprcubd vs. Microsoft Azure Cosmos DB vs. Yanza vs. YottaDB

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Serverless Time Series DBMS

Globally distributed, horizontally scalable, multi-model database service

Time Series DBMS for IoT Applications

A fast and solid embedded Key-value store

Primary database model

Document store
Key-value store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Key-value store

Secondary database models

Spatial DBMS

Relational DBMS

using the Octo plugin

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	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

aws.amazon.com/dynamodb

hyprcubd.com (offline)

azure.microsoft.com/services/cosmos-db

yanza.com

yottadb.com

Technical documentation

docs.aws.amazon.com/dynamodb

learn.microsoft.com/azure/cosmos-db

yottadb.com/resources/documentation

Developer

Amazon

Hyprcubd, Inc.

Microsoft

Yanza

YottaDB, LLC

Initial release

2012

2014

2015

2001

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free version available

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

hosted

Windows

Docker
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

JSON types

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 properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

by using the Octo plugin

APIs and other access methods

RESTful HTTP API

gRPC (https)

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

any language that supports HTTP calls

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

JavaScript

Triggers

yes

by integration with AWS Lambda

JavaScript

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

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.

yes

User concepts

Access control

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

token access

Access rights can be defined down to the item level

Users and groups based on OS-security mechanisms

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