DBMS > Firebase Realtime Database vs. SQLite vs. Titan vs. VoltDB vs. WakandaDB

System Properties Comparison Firebase Realtime Database vs. SQLite vs. Titan vs. VoltDB vs. WakandaDB

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

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

Widely used embeddable, in-process RDBMS

Titan is a Graph DBMS optimized for distributed clusters.

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

firebase.google.com/products/realtime-database

www.sqlite.org

github.com/thinkaurelius/titan

www.voltdb.com

wakanda.github.io

Technical documentation

firebase.google.com/docs/database

www.sqlite.org/docs.html

github.com/thinkaurelius/titan/wiki

docs.voltdb.com

wakanda.github.io/doc

Developer

Google

acquired by Google 2014

Dwayne Richard Hipp

Aurelius, owned by DataStax

VoltDB Inc.

Wakanda SAS

Initial release

2012

2000

2012

2010

2012

Current release

3.46.0 (23 May 2024), May 2024

11.3, April 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Public Domain

Open Source

Apache license, version 2.0

Open Source

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

Open Source

AGPLv3, extended commercial license 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

Java, C++

C++, JavaScript

Server operating systems

hosted

server-less

Linux
OS X
Unix
Windows

Linux
OS X

for development

Linux
OS X
Windows

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

yes

only a subset of SQL 99

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Java API
JDBC
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

Java
JavaScript
Objective-C

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Clojure
Java
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

JavaScript

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Java

yes

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

via pluggable storage backends

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

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
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

Snapshots and command logging

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

User authentification and security via Rexster Graph Server

Users and roles with access to stored procedures

yes

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