DBMS > AgensGraph vs. AnzoGraph DB vs. EJDB vs. Oracle NoSQL

System Properties Comparison AgensGraph vs. AnzoGraph DB vs. EJDB vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Graph DBMS
Relational DBMS

Graph DBMS
RDF store

Document store

Document store
Key-value store
Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

bitnine.net/agensgraph

cambridgesemantics.com/anzograph

github.com/Softmotions/ejdb

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

bitnine.net/documentation

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

github.com/Softmotions/ejdb/blob/master/README.md

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Bitnine Global Inc.

Cambridge Semantics

Softmotions

Oracle

Initial release

2016

2018

2012

2011

Current release

2.1, December 2018

2.3, January 2021

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free trial version available

Open Source

GPLv2

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Java

Server operating systems

Linux
OS X
Windows

Linux

server-less

Linux
Solaris SPARC/x86

Data scheme

depending on used data model

Schema-free and OWL/RDFS-schema support

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

optional

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

yes

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

SQL-like DML and DDL statements

APIs and other access methods

Cypher Query Language
JDBC

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

in-process shared library

RESTful HTTP API

Supported programming languages

C
Java
JavaScript
Python

C++
Java
Python

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

Triggers

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Automatic sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication in MPP-Cluster

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

not needed in graphs

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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