DBMS > 4D vs. AnzoGraph DB vs. HarperDB vs. Oracle

System Properties Comparison 4D vs. AnzoGraph DB vs. HarperDB vs. Oracle

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Widely used RDBMS

Primary database model

Secondary database models

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	2.47
Rank	#110	Overall
	#54	Relational DBMS

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

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

www.4d.com

cambridgesemantics.com/anzograph

www.harperdb.io

www.oracle.com/database

Technical documentation

developer.4d.com

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

docs.harperdb.io/docs

docs.oracle.com/en/database

Developer

4D, Inc

Cambridge Semantics

HarperDB

Oracle

Initial release

1984

2018

2017

1980

Current release

v20, April 2023

2.3, January 2021

3.1, August 2021

23c, September 2023

License

Commercial or Open Source

commercial

free trial version available

commercial

free community edition available

commercial

restricted free version is available

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

Node.js

C and C++

Server operating systems

OS X
Windows

Linux

Linux
OS X

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

Data scheme

yes

Schema-free and OWL/RDFS-schema support

dynamic schema

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes

JSON data types

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

yes

close to SQL 92

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

SQL-like data manipulation statements

yes

with proprietary extensions

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

4D proprietary IDE
PHP

C++
Java
Python

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

Custom Functions

since release 3.1

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

A table resides as a whole on one (or more) nodes in a cluster

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication in MPP-Cluster

yes

the nodes on which a table resides can be defined

Multi-source replication
Source-replica replication

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

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

not needed in graphs

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomic execution of specific operations

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

Users and groups

Access rights for users and roles

fine grained access rights according to SQL-standard

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