DBMS > AnzoGraph DB vs. MaxDB vs. Spark SQL vs. SpatiaLite

System Properties Comparison AnzoGraph DB vs. MaxDB vs. Spark SQL vs. SpatiaLite

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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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Spatial extension of SQLite

Primary database model

Graph DBMS
RDF store

Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

cambridgesemantics.com/anzograph

maxdb.sap.com

spark.apache.org/sql

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

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

maxdb.sap.com/documentation

spark.apache.org/docs/latest/sql-programming-guide.html

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Cambridge Semantics

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

Apache Software Foundation

Alessandro Furieri

Initial release

2018

1984

2014

2008

Current release

2.3, January 2021

7.9.10.12, February 2024

3.5.0 ( 2.13), September 2023

5.0.0, August 2020

License

Commercial or Open Source

commercial

free trial version available

commercial

Limited community edition free

Open Source

Apache 2.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Scala

C++

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

server-less

Data scheme

Schema-free and OWL/RDFS-schema support

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.

Secondary indexes

yes

SQL

Support of SQL

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

yes

SQL-like DML and DDL statements

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

JDBC
ODBC

Supported programming languages

C++
Java
Python

.Net
C#
Java
Perl
PHP
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

none

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

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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