DBMS > AnzoGraph DB vs. Microsoft Azure Cosmos DB vs. Netezza vs. Snowflake vs. Transbase

System Properties Comparison AnzoGraph DB vs. Microsoft Azure Cosmos DB vs. Netezza vs. Snowflake vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Globally distributed, horizontally scalable, multi-model database service

Data warehouse and analytics appliance part of IBM PureSystems

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

cambridgesemantics.com/anzograph

azure.microsoft.com/services/cosmos-db

www.ibm.com/products/netezza

www.snowflake.com

www.transaction.de/en/products/transbase.html

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

learn.microsoft.com/azure/cosmos-db

docs.snowflake.net/manuals/index.html

www.transaction.de/en/products/transbase/features.html

Developer

Cambridge Semantics

Microsoft

IBM

Snowflake Computing Inc.

Transaction Software GmbH

Initial release

2018

2014

2000

2014

1987

Current release

2.3, January 2021

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

free development license

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 and C++

Server operating systems

Linux

hosted

Linux

included in appliance

hosted

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like query language

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++
Java
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

JavaScript

yes

user defined functions

yes

Triggers

JavaScript

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Implicit feature of the cloud service

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Implicit feature of the cloud service

Source-replica replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

yes

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

Access rights for users and roles

Access rights can be defined down to the item level

Users with fine-grained authorization concept

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

fine grained access rights according to SQL-standard

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