DBMS > AnzoGraph DB vs. InterSystems Caché vs. Snowflake vs. Ultipa

System Properties Comparison AnzoGraph DB vs. InterSystems Caché vs. Snowflake vs. Ultipa

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Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

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

A multi-model DBMS and application server

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

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Graph DBMS
RDF store

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Graph DBMS

Secondary database models

Document store

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

cambridgesemantics.com/anzograph

www.intersystems.com/products/cache

www.snowflake.com

www.ultipa.com

Technical documentation

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

docs.intersystems.com

docs.snowflake.net/manuals/index.html

www.ultipa.com/document

Developer

Cambridge Semantics

InterSystems

Snowflake Computing Inc.

Ultipa

Initial release

2018

1997

2014

2019

Current release

2.3, January 2021

2018.1.4, May 2020

License

Commercial or Open Source

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Server operating systems

Linux

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

depending on used data model

yes

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

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

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

yes

APIs and other access methods

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

.NET Client API
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C++
Java
Python

C#
C++
Java

JavaScript (Node.js)
Python

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

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

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 for users, groups and roles

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

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