DBMS > Amazon Redshift vs. BigObject vs. H2GIS vs. Oracle Coherence

System Properties Comparison Amazon Redshift vs. BigObject vs. H2GIS vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

Spatial extension of H2

Oracles in-memory data grid solution

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Spatial DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Website

aws.amazon.com/redshift

bigobject.io

www.h2gis.org

www.oracle.com/java/coherence

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

www.h2gis.org/docs/home

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

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

CNRS

Oracle

Initial release

2012

2015

2013

2007

Current release

14.1, August 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

LGPL 3.0

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

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

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

JCache
JPA
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

yes

based on H2

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

based on H2

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

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, multi-version concurrency control (MVCC)

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

yes

based on H2

authentification to access the cache via certificates or http basic authentication

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