DBMS > Amazon DynamoDB vs. GridGain vs. Microsoft Azure Cosmos DB vs. WakandaDB

System Properties Comparison Amazon DynamoDB vs. GridGain vs. Microsoft Azure Cosmos DB vs. WakandaDB

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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

GridGain is an in-memory computing platform, built on Apache Ignite

Globally distributed, horizontally scalable, multi-model database service

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store
Key-value store

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Object oriented DBMS

Secondary database models

Spatial 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	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

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

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

aws.amazon.com/dynamodb

www.gridgain.com

azure.microsoft.com/services/cosmos-db

wakanda.github.io

Technical documentation

docs.aws.amazon.com/dynamodb

www.gridgain.com/docs/index.html

learn.microsoft.com/azure/cosmos-db

wakanda.github.io/doc

Developer

Amazon

GridGain Systems, Inc.

Microsoft

Wakanda SAS

Initial release

2012

2007

2014

2012

Current release

GridGain 8.5.1

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

AGPLv3, extended commercial license available

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++, .Net

C++, JavaScript

Server operating systems

hosted

Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

APIs and other access methods

RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

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

JavaScript

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

JavaScript

yes

Triggers

yes

by integration with AWS Lambda

yes (cache interceptors and events)

JavaScript

yes

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

yes (replicated cache)

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes (compute grid and hadoop accelerator)

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

Immediate 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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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.

yes

User concepts

Access control

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

Security Hooks for custom implementations

Access rights can be defined down to the item level

yes

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