DBMS > AgensGraph vs. Amazon Neptune vs. Microsoft Azure Table Storage vs. Snowflake vs. Valentina Server

System Properties Comparison AgensGraph vs. Amazon Neptune vs. Microsoft Azure Table Storage vs. Snowflake vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

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

Fast, reliable graph database built for the cloud

A Wide Column Store for rapid development using massive semi-structured datasets

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

Object-relational database and reports server

Primary database model

Graph DBMS
Relational DBMS

Graph DBMS
RDF store

Wide column store

Relational DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/neptune

azure.microsoft.com/en-us/services/storage/tables

www.snowflake.com

www.valentina-db.net

Technical documentation

bitnine.net/documentation

aws.amazon.com/neptune/developer-resources

docs.snowflake.net/manuals/index.html

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

Developer

Bitnine Global Inc.

Amazon

Microsoft

Snowflake Computing Inc.

Paradigma Software

Initial release

2016

2017

2012

2014

1999

Current release

2.1, December 2018

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

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

depending on used data model

schema-free

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Cypher Query Language
JDBC

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

RESTful HTTP API

CLI Client
JDBC
ODBC

ODBC

Supported programming languages

C
Java
JavaScript
Python

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

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

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

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)

Access rights based on private key authentication or shared access signatures

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

fine grained access rights according to SQL-standard

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