DBMS > AnzoGraph DB vs. MaxDB vs. Microsoft Azure AI Search vs. Oracle vs. Snowflake

System Properties Comparison AnzoGraph DB vs. MaxDB vs. Microsoft Azure AI Search vs. Oracle vs. Snowflake

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

A robust and reliable RDBMS optimized to run all major SAP solutions

Search-as-a-service for web and mobile app development

Widely used RDBMS

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

Primary database model

Secondary database models

Vector DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

cambridgesemantics.com/anzograph

maxdb.sap.com

azure.microsoft.com/en-us/services/search

www.oracle.com/database

www.snowflake.com

Technical documentation

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

maxdb.sap.com/documentation

learn.microsoft.com/en-us/azure/search

docs.oracle.com/en/database

docs.snowflake.net/manuals/index.html

Developer

Cambridge Semantics

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

Oracle

Snowflake Computing Inc.

Initial release

2018

1984

2015

1980

2014

Current release

2.3, January 2021

7.9.10.12, February 2024

23c, September 2023

License

Commercial or Open Source

commercial

free trial version available

commercial

Limited community edition free

commercial

restricted free version is available

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++

C and C++

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Schemaless in JSON and XML columns

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

with proprietary extensions

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC
WebDAV

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
Python

.Net
C#
Java
Perl
PHP
Python

C#
Java
JavaScript
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

PL/SQL

also stored procedures in Java possible

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

can be realized in PL/SQL

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

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

yes

using Azure authentication

fine grained access rights according to SQL-standard

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

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