DBMS > Amazon DocumentDB vs. GigaSpaces vs. NuoDB vs. Snowflake

System Properties Comparison Amazon DocumentDB vs. GigaSpaces vs. NuoDB vs. Snowflake

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Editorial information provided by DB-Engines

Name

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

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

aws.amazon.com/documentdb

www.gigaspaces.com

www.3ds.com/nuodb-distributed-sql-database

www.snowflake.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.gigaspaces.com/latest/landing.html

doc.nuodb.com

docs.snowflake.net/manuals/index.html

Developer

Gigaspaces Technologies

Dassault Systèmes

originally NuoDB, Inc.

Snowflake Computing Inc.

Initial release

2019

2000

2013

2014

Current release

15.5, September 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

commercial

limited edition free

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++, .Net

C++

Server operating systems

hosted

Linux
macOS
Solaris
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

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

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
C++
Java
Python
Scala

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Java, SQL

user defined functions

Triggers

yes, event driven architecture

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

data is dynamically stored/cached on the nodes where it is read/written

yes

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

yes

Managed transparently by NuoDB

yes

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

yes

Transaction concepts

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

Atomic single-document operations

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

User concepts

Access control

Access rights for users and roles

Role-based access control

Standard SQL roles/ privileges, Administrative Users

Users with fine-grained authorization concept, user roles and pluggable authentication

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