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

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

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Natively in-memory DBMS with options for persistency, high-availability and clustering

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 general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

Document store

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	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

bigobject.io

www.mcobject.com

firebase.google.com/products/realtime-database

www.h2database.com

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

Technical documentation

docs.bigobject.io

www.mcobject.com/docs/extremedb.htm

firebase.google.com/docs/database

www.h2database.com/html/main.html

www.xtdb.com/docs

Developer

BigObject, Inc.

McObject

Google

acquired by Google 2014

Thomas Mueller

Juxt Ltd.

Initial release

2015

2001

2012

2005

2019

Current release

8.2, 2021

2.2.220, July 2023

1.19, September 2021

License

Commercial or Open Source

commercial

free community edition available

commercial

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

C and C++

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)

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

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.

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with the option: eXtremeSQL

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

Java
JavaScript
Objective-C

Java

Clojure
Java

Server-side scripts

Stored procedures

Lua

yes

limited functionality with using 'rules'

Java Stored Procedures and User-Defined Functions

Triggers

yes

by defining events

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning / sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

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

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

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