DBMS > AnzoGraph DB vs. HEAVY.AI vs. IBM Db2 vs. MaxDB vs. Snowflake

System Properties Comparison AnzoGraph DB vs. HEAVY.AI vs. IBM Db2 vs. MaxDB 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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Common in IBM host environments, 2 different versions for host and Windows/Linux

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

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

Primary database model

Graph DBMS
RDF store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

cambridgesemantics.com/anzograph

github.com/heavyai/heavydb
www.heavy.ai

www.ibm.com/products/db2

maxdb.sap.com

www.snowflake.com

Technical documentation

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

docs.heavy.ai

www.ibm.com/docs/en/db2

maxdb.sap.com/documentation

docs.snowflake.net/manuals/index.html

Developer

Cambridge Semantics

HEAVY.AI, Inc.

IBM

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

Snowflake Computing Inc.

Initial release

2018

2016

1983

host version

1984

2014

Current release

2.3, January 2021

5.10, January 2022

12.1, October 2016

7.9.10.12, February 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2; enterprise edition available

commercial

free version is available

commercial

Limited community edition free

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++ and CUDA

C and C++

C++

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

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

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

ADO.NET
JDBC
ODBC
WebDAV

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
Python

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
C#
Java
Perl
PHP
Python

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

Sharding

Round robin

Sharding

only with Windows/Unix/Linux Version

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

yes

with separate tools (MQ, InfoSphere)

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

fine grained access rights according to SQL-standard

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

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