DBMS > Apache Phoenix vs. Google Cloud Firestore vs. TerarkDB

System Properties Comparison Apache Phoenix vs. Google Cloud Firestore vs. TerarkDB

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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.

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Document store

Key-value store

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

phoenix.apache.org

firebase.google.com/products/firestore

github.com/bytedance/terarkdb

Technical documentation

phoenix.apache.org

firebase.google.com/docs/firestore

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Google

ByteDance, originally Terark

Initial release

2014

2017

2016

Current release

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

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted open source version 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.

Implementation language

Java

C++

Server operating systems

Linux
Unix
Windows

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

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

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC

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

C++ API
Java API

Supported programming languages

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

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

C++
Java

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

Triggers

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

Multi-source replication
Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

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.

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More resources

DB-Engines blog posts

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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

What Is HBase? (Definition, Uses, Benefits, Features)
22 December 2022, Built In

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

Azure HDInsight Analytics Platform Now Supports Apache Hadoop 3.0
18 April 2019, eWeek

provided by Google News

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google's Cloud Firestore is now generally available
31 January 2019, ZDNet

Google launches Cloud Firestore, a new document database for app developers
3 October 2017, TechCrunch

Google Cloud adds vector support to all its database offerings
29 February 2024, InfoWorld

provided by Google News

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