DBMS > Firebase Realtime Database vs. H2 vs. Microsoft Azure Table Storage vs. TimesTen vs. XTDB

System Properties Comparison Firebase Realtime Database vs. H2 vs. Microsoft Azure Table Storage vs. TimesTen vs. XTDB

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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A Wide Column Store for rapid development using massive semi-structured datasets

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

firebase.google.com/products/realtime-database

www.h2database.com

azure.microsoft.com/en-us/services/storage/tables

www.oracle.com/database/technologies/related/timesten.html

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

Technical documentation

firebase.google.com/docs/database

www.h2database.com/html/main.html

docs.oracle.com/en/database/other-databases/timesten/index.html

www.xtdb.com/docs

Developer

Google

acquired by Google 2014

Thomas Mueller

Microsoft

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Juxt Ltd.

Initial release

2012

2005

2012

1998

2019

Current release

2.2.220, July 2023

Release 22.1

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

MIT License

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

Clojure

Server operating systems

hosted

All OS with a Java VM

hosted

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

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

Data scheme

schema-free

yes

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

RESTful HTTP API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

HTTP REST
JDBC

Supported programming languages

Java
JavaScript
Objective-C

Java

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Java
Node.js
PL/SQL
Python

Clojure
Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Java Stored Procedures and User-Defined Functions

PL/SQL

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

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 or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

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

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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