DBMS > Apache Phoenix vs. Google Cloud Firestore vs. Oracle vs. Sadas Engine

System Properties Comparison Apache Phoenix vs. Google Cloud Firestore vs. Oracle vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Document store

Relational DBMS

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

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

phoenix.apache.org

firebase.google.com/products/firestore

www.oracle.com/database

www.sadasengine.com

Technical documentation

phoenix.apache.org

firebase.google.com/docs/firestore

docs.oracle.com/en/database

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Apache Software Foundation

Google

Oracle

SADAS s.r.l.

Initial release

2014

2017

1980

2006

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

23c, September 2023

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

free trial version available

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

C and C++

C++

Server operating systems

Linux
Unix
Windows

hosted

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

AIX
Linux
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

Schemaless in JSON and XML columns

yes

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

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC
Proprietary protocol

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

PL/SQL

also stored procedures in Java possible

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Using Cloud Dataflow

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

isolation level can be parameterized

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

managed by 'Learn by Usage'

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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, groups and roles according to SQL-standard

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