DBMS > AnzoGraph DB vs. Greenplum vs. MaxDB vs. Oracle vs. Sequoiadb

System Properties Comparison AnzoGraph DB vs. Greenplum vs. MaxDB vs. Oracle vs. Sequoiadb

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

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

Widely used RDBMS

NewSQL database with distributed OLTP and SQL

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store
Spatial 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	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

cambridgesemantics.com/anzograph

greenplum.org

maxdb.sap.com

www.oracle.com/database

www.sequoiadb.com

Technical documentation

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

docs.greenplum.org

maxdb.sap.com/documentation

docs.oracle.com/en/database

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Cambridge Semantics

Pivotal Software Inc.

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

Oracle

Sequoiadb Ltd.

Initial release

2018

2005

1984

1980

2013

Current release

2.3, January 2021

7.0.0, September 2023

7.9.10.12, February 2024

23c, September 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

commercial

Limited community edition free

commercial

restricted free version is available

Open Source

Server: AGPL; Client: Apache V2

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++

C and C++

C++

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

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

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

since Version 4.2

yes

Secondary indexes

yes

SQL

Support of SQL

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

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

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

JDBC
ODBC

ADO.NET
JDBC
ODBC
WebDAV

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

proprietary protocol using JSON

Supported programming languages

C++
Java
Python

C
Java
Perl
Python
R

.Net
C#
Java
Perl
PHP
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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

PL/SQL

also stored procedures in Java possible

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual 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

Document is locked during a transaction

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

simple password-based access control

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