DBMS > Amazon Redshift vs. EXASOL vs. Google Cloud Firestore vs. TinkerGraph

System Properties Comparison Amazon Redshift vs. EXASOL vs. Google Cloud Firestore vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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.

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Document store

Graph DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

aws.amazon.com/redshift

www.exasol.com

firebase.google.com/products/firestore

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.aws.amazon.com/redshift

www.exasol.com/resources

firebase.google.com/docs/firestore

Developer

Amazon (based on PostgreSQL)

Exasol

Google

Initial release

2012

2000

2017

2009

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

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

yes

APIs and other access methods

JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

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

TinkerPop 3

Supported programming languages

All languages supporting JDBC/ODBC

Java
Lua
Python
R

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

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes, Firebase Rules & Cloud Functions

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

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 for users, groups and roles according to SQL-standard

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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