DBMS > AgensGraph vs. Amazon Redshift vs. InfinityDB vs. Valentina Server

System Properties Comparison AgensGraph vs. Amazon Redshift vs. InfinityDB vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Large scale data warehouse service for use with business intelligence tools

A Java embedded Key-Value Store which extends the Java Map interface

Object-relational database and reports server

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Key-value store

Relational DBMS

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

Score	0.17
Rank	#320	Overall
	#29	Graph DBMS
	#143	Relational DBMS

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.00
Rank	#383	Overall
	#59	Key-value stores

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/redshift

boilerbay.com

www.valentina-db.net

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/redshift

boilerbay.com/infinitydb/manual

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

Developer

Bitnine Global Inc.

Amazon (based on PostgreSQL)

Boiler Bay Inc.

Paradigma Software

Initial release

2016

2012

2002

1999

Current release

2.1, December 2018

4.0

5.7.5

License

Commercial or Open Source

Open Source

Apache License 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

Linux
OS X
Windows

hosted

All OS with a Java VM

Linux
OS X
Windows

Data scheme

depending on used data model

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

yes

restricted

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ODBC

Supported programming languages

C
Java
JavaScript
Python

All languages supporting JDBC/ODBC

Java

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

Server-side scripts

Stored procedures

yes

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

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