DBMS > BigObject vs. Firebase Realtime Database vs. Geode vs. H2 vs. XTDB

System Properties Comparison BigObject vs. Firebase Realtime Database vs. Geode vs. H2 vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

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

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

bigobject.io

firebase.google.com/products/realtime-database

geode.apache.org

www.h2database.com

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

Technical documentation

docs.bigobject.io

firebase.google.com/docs/database

geode.apache.org/docs

www.h2database.com/html/main.html

www.xtdb.com/docs

Developer

BigObject, Inc.

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.

Thomas Mueller

Juxt Ltd.

Initial release

2015

2012

2002

2005

2019

Current release

1.1, February 2017

2.2.220, July 2023

1.19, September 2021

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

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

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

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

All OS with a Java VM

the JDK (8 or later) is also required

All OS with a Java VM

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

Data scheme

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

SQL-like DML and DDL statements

SQL-like query language (OQL)

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

Java
JavaScript
Objective-C

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

Java

Clojure
Java

Server-side scripts

Stored procedures

Lua

limited functionality with using 'rules'

user defined functions

Java Stored Procedures and User-Defined Functions

Triggers

Callbacks are triggered when data changes

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

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

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

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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

Read/write lock on objects (tables, trees)

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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

Access rights per client and object definable

fine grained access rights according to SQL-standard

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More resources

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