DBMS > Google Cloud Firestore vs. Hive vs. VoltDB

System Properties Comparison Google Cloud Firestore vs. Hive vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

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.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store

Relational DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

firebase.google.com/products/firestore

hive.apache.org

www.voltdb.com

Technical documentation

firebase.google.com/docs/firestore

cwiki.apache.org/confluence/display/Hive/Home

docs.voltdb.com

Developer

Google

Apache Software Foundation

initially developed by Facebook

VoltDB Inc.

Initial release

2017

2012

2010

Current release

3.1.3, April 2022

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

hosted

All OS with a Java VM

Linux
OS X

for development

Data scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

only a subset of SQL 99

APIs and other access methods

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

JDBC
ODBC
Thrift

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

C++
Java
PHP
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

user defined functions and integration of map-reduce

Java

Triggers

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

User concepts

Access control

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

Access rights for users, groups and roles

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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Recent citations in the 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 Firebase gets AI extensions, opens up its marketplace
10 May 2023, TechCrunch

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

Firestore and Python | NoSQL on Google Cloud
7 August 2020, Towards Data Science

provided by Google News

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Apache Software Foundation Announces Apache Hive 4.0
30 April 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

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1 May 2024, Simplilearn

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24 January 2024, TechTarget

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16 October 2023, YourStory

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Aims for Fast Big Data Development -- ADTmag
29 January 2015, ADT Magazine

provided by Google News

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