DBMS > Amazon Neptune vs. Netezza vs. OpenEdge vs. Snowflake vs. TigerGraph

System Properties Comparison Amazon Neptune vs. Netezza vs. OpenEdge vs. Snowflake vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Data warehouse and analytics appliance part of IBM PureSystems

Application development environment with integrated database management system

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Graph DBMS
RDF store

Relational DBMS

Graph DBMS

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

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

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/neptune

www.ibm.com/products/netezza

www.progress.com/openedge

www.snowflake.com

www.tigergraph.com

Technical documentation

aws.amazon.com/neptune/developer-resources

documentation.progress.com/output/ua/OpenEdge_latest

docs.snowflake.net/manuals/index.html

docs.tigergraph.com

Developer

Amazon

IBM

Progress Software Corporation

Snowflake Computing Inc.

Initial release

2017

2000

1984

2014

2017

Current release

OpenEdge 12.2, March 2020

License

Commercial or Open Source

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

C++

Server operating systems

hosted

Linux

included in appliance

AIX
HP-UX
Linux
Solaris
Windows

hosted

Linux

Data scheme

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

close to SQL 92

yes

SQL-like query language (GSQL)

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC
OLE DB

JDBC
ODBC

CLI Client
JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

Progress proprietary ABL (Advanced Business Language)

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

since Version 11.4

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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.

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

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.

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

Users and groups

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

Role-based access control

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