DBMS > Firebase Realtime Database vs. Hive vs. ReductStore vs. XTDB

System Properties Comparison Firebase Realtime Database vs. Hive vs. ReductStore vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

firebase.google.com/products/realtime-database

hive.apache.org

github.com/reductstore
www.reduct.store

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

firebase.google.com/docs/database

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

www.reduct.store/docs

www.xtdb.com/docs

Developer

Google

acquired by Google 2014

Apache Software Foundation

initially developed by Facebook

ReductStore LLC

Juxt Ltd.

Initial release

2012

2023

2019

Current release

3.1.3, April 2022

1.9, March 2024

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Business Source License 1.1

Open Source

MIT License

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++, Rust

Clojure

Server operating systems

hosted

All OS with a Java VM

Docker
Linux
macOS
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
Thrift

HTTP API

HTTP REST
JDBC

Supported programming languages

Java
JavaScript
Objective-C

C++
Java
PHP
Python

C++
JavaScript (Node.js)
Python
Rust

Clojure
Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

user defined functions and integration of map-reduce

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

User concepts

Access control

yes, based on authentication and database rules

Access rights for users, groups and roles

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More resources

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