DBMS > Amazon DocumentDB vs. GigaSpaces vs. Yanza

System Properties Comparison Amazon DocumentDB vs. GigaSpaces vs. Yanza

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Editorial information provided by DB-Engines

Name

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

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Time Series DBMS for IoT Applications

Primary database model

Document store

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Secondary database models

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Trend Chart

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Website

aws.amazon.com/documentdb

www.gigaspaces.com

yanza.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.gigaspaces.com/latest/landing.html

Developer

Gigaspaces Technologies

Yanza

Initial release

2019

2000

2015

Current release

15.5, September 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

commercial

free version available

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

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Implementation language

Java, C++, .Net

Server operating systems

hosted

Linux
macOS
Solaris
Windows

Windows

Data scheme

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
C++
Java
Python
Scala

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-document operations

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

Role-based access control

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More resources

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