DBMS > AgensGraph vs. Amazon Redshift vs. BigObject vs. Oracle Coherence

System Properties Comparison AgensGraph vs. Amazon Redshift vs. BigObject vs. Oracle Coherence

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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

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

Oracles in-memory data grid solution

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

bitnine.net/agensgraph

aws.amazon.com/redshift

bigobject.io

www.oracle.com/java/coherence

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

docs.oracle.com/en/middleware/standalone/coherence

Developer

Bitnine Global Inc.

Amazon (based on PostgreSQL)

BigObject, Inc.

Oracle

Initial release

2016

2012

2015

2007

Current release

2.1, December 2018

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free community edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Windows

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Data scheme

depending on used data model

yes

schema-free

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

JCache
JPA
RESTful HTTP API

Supported programming languages

C
Java
JavaScript
Python

All languages supporting JDBC/ODBC

.Net
C++
Java

Server-side scripts

Stored procedures

yes

user defined functions

in Python

Lua

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

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