DBMS > Amazon Redshift vs. Google Cloud Firestore vs. Oracle vs. ScyllaDB

System Properties Comparison Amazon Redshift vs. Google Cloud Firestore vs. Oracle vs. ScyllaDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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.

Widely used RDBMS

Cassandra and DynamoDB compatible wide column store

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Key-value store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Website

aws.amazon.com/redshift

firebase.google.com/products/firestore

www.oracle.com/database

www.scylladb.com

Technical documentation

docs.aws.amazon.com/redshift

firebase.google.com/docs/firestore

docs.oracle.com/en/database

docs.scylladb.com

Developer

Amazon (based on PostgreSQL)

Google

Oracle

ScyllaDB

Initial release

2012

2017

1980

2015

Current release

23c, September 2023

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Open Source (AGPL), commercial license available

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.

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

C and C++

C++

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

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.

yes

Secondary indexes

restricted

yes

cluster global secondary indices

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

SQL-like DML and DDL statements (CQL)

APIs and other access methods

JDBC
ODBC

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes, Firebase Rules & Cloud Functions

PL/SQL

also stored procedures in Java possible

yes, Lua

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Multi-source replication
Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

yes

ACID

isolation level can be parameterized

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

in-memory tables

User concepts

Access control

fine grained access rights 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.

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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