DBMS > Firebase Realtime Database vs. Geode vs. JanusGraph vs. SQLite vs. TimesTen

System Properties Comparison Firebase Realtime Database vs. Geode vs. JanusGraph vs. SQLite vs. TimesTen

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.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Widely used embeddable, in-process RDBMS

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.

Primary database model

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

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	1.51
Rank	#147	Overall
	#25	Key-value stores

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

firebase.google.com/products/realtime-database

geode.apache.org

janusgraph.org

www.sqlite.org

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

Technical documentation

firebase.google.com/docs/database

geode.apache.org/docs

docs.janusgraph.org

www.sqlite.org/docs.html

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

Developer

Google

acquired by Google 2014

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Linux Foundation; originally developed as Titan by Aurelius

Dwayne Richard Hipp

Oracle

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

Initial release

2012

2002

2017

2000

1998

Current release

1.1, February 2017

1.0.0, October 2023

3.46.1 (13 August 2024), August 2024

Release 22.1

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache 2.0

Open Source

Public Domain

commercial

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

Server operating systems

hosted

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Unix
Windows

server-less

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

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

SQL-like query language (OQL)

yes

SQL-92 is not fully supported

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Supported programming languages

Java
JavaScript
Objective-C

.Net
All JVM based languages
C++
Groovy
Java
Scala

Clojure
Java
Python

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

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

yes

PL/SQL

Triggers

Callbacks are triggered when data changes

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

Multi-source replication
Source-replica replication

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

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

yes

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

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

yes

by means of logfiles and checkpoints

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

Access rights per client and object definable

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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