DBMS > Amazon Redshift vs. BigObject vs. Geode vs. Google Cloud Firestore

System Properties Comparison Amazon Redshift vs. BigObject vs. Geode vs. Google Cloud Firestore

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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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Document store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Website

aws.amazon.com/redshift

bigobject.io

geode.apache.org

firebase.google.com/products/firestore

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

geode.apache.org/docs

firebase.google.com/docs/firestore

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Google

Initial release

2012

2015

2002

2017

Current release

1.1, February 2017

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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

the JDK (8 or later) is also required

hosted

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

SQL-like query language (OQL)

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
All JVM based languages
C++
Groovy
Java
Scala

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

user defined functions

yes, Firebase Rules & Cloud Functions

Triggers

yes

Cache Event Listeners

yes, with Cloud Functions

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

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

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

yes, on a single node

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights per client and object definable

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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