DBMS > Firebase Realtime Database vs. Hypertable vs. IRONdb vs. XTDB vs. YottaDB

System Properties Comparison Firebase Realtime Database vs. Hypertable vs. IRONdb vs. XTDB vs. YottaDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

firebase.google.com/products/realtime-database

www.circonus.com/solutions/time-series-database/

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

yottadb.com

Technical documentation

firebase.google.com/docs/database

docs.circonus.com/irondb/category/getting-started

www.xtdb.com/docs

yottadb.com/resources/documentation

Developer

Google

acquired by Google 2014

Hypertable Inc.

Circonus LLC.

Juxt Ltd.

YottaDB, LLC

Initial release

2012

2009

2017

2019

2001

Current release

0.9.8.11, March 2016

V0.10.20, January 2018

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

commercial

Open Source

MIT License

Open Source

AGPL 3.0

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

C++

C and C++

Clojure

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux

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

Docker
Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

limited SQL, making use of Apache Calcite

by using the Octo plugin

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

C++ API
Thrift

HTTP API

HTTP REST
JDBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Java
JavaScript
Objective-C

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Clojure
Java

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes, in Lua

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

configurable replication factor, datacenter aware

yes, each node contains all data

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

optimistic locking

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

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

yes, based on authentication and database rules

Users and groups based on OS-security mechanisms

More information provided by the system vendor

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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