DBMS > Amazon DynamoDB vs. Netezza vs. OrigoDB vs. Postgres-XL vs. Snowflake

System Properties Comparison Amazon DynamoDB vs. Netezza vs. OrigoDB vs. Postgres-XL vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Data warehouse and analytics appliance part of IBM PureSystems

A fully ACID in-memory object graph database

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

aws.amazon.com/dynamodb

www.ibm.com/products/netezza

origodb.com

www.postgres-xl.org

www.snowflake.com

Technical documentation

docs.aws.amazon.com/dynamodb

origodb.com/docs

www.postgres-xl.org/documentation

docs.snowflake.net/manuals/index.html

Developer

Amazon

IBM

Robert Friberg et al

Snowflake Computing Inc.

Initial release

2012

2000

2009

under the name LiveDB

2014

since 2012, originally named StormDB

2014

Current release

10 R1, October 2018

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Mozilla public license

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

Server operating systems

hosted

Linux

included in appliance

Linux
Windows

Linux
macOS

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

User defined using .NET types and collections

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.

can be achieved using .NET

yes

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
OLE DB

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

Domain Events

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

depending on model

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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)

Users with fine-grained authorization concept

Role based authorization

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.