DBMS > Amazon Redshift vs. Amazon SimpleDB vs. HugeGraph vs. Valentina Server

System Properties Comparison Amazon Redshift vs. Amazon SimpleDB vs. HugeGraph vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

A fast-speed and highly-scalable Graph DBMS

Object-relational database and reports server

Primary database model

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

aws.amazon.com/redshift

aws.amazon.com/simpledb

github.com/hugegraph
hugegraph.apache.org

www.valentina-db.net

Technical documentation

docs.aws.amazon.com/redshift

docs.aws.amazon.com/simpledb

hugegraph.apache.org/docs

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Amazon (based on PostgreSQL)

Amazon

Baidu

Paradigma Software

Initial release

2012

2007

2018

1999

Current release

0.9

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

Server operating systems

hosted

Linux
macOS
Unix

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

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.

Secondary indexes

restricted

yes

All columns are indexed automatically

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Groovy
Java
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

in Python

asynchronous Gremlin script jobs

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding must be implemented in the application

yes

depending on used storage backend, e.g. Cassandra and HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

edges in graph

yes

Transaction concepts

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

ACID

Concurrent data updates can be detected by the application

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

fine grained access rights according to SQL-standard

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

Users, roles and permissions

fine grained access rights according to SQL-standard

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