DBMS > Apache Impala vs. BigchainDB vs. eXtremeDB vs. Firebase Realtime Database vs. ToroDB

System Properties Comparison Apache Impala vs. BigchainDB vs. eXtremeDB vs. Firebase Realtime Database vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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.

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Document store

Relational DBMS
Time Series DBMS

Document store

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Website

impala.apache.org

www.bigchaindb.com

www.mcobject.com

firebase.google.com/products/realtime-database

github.com/torodb/server

Technical documentation

impala.apache.org/impala-docs.html

bigchaindb.readthedocs.io/en/latest

www.mcobject.com/docs/extremedb.htm

firebase.google.com/docs/database

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

McObject

Google

acquired by Google 2014

8Kdata

Initial release

2013

2016

2001

2012

2016

Current release

4.1.0, June 2022

8.2, 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL v3

commercial

Open Source

AGPL-V3

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++

Python

C and C++

Java

Server operating systems

Linux

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

All OS with a Java 7 VM

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

APIs and other access methods

JDBC
ODBC

CLI Client
RESTful HTTP API

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

Android
iOS
JavaScript API
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Go
Haskell
Java
JavaScript
Python
Ruby

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

Java
JavaScript
Objective-C

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

limited functionality with using 'rules'

Triggers

yes

by defining events

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning / sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

yes, based on authentication and database rules

Access rights for users and roles

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...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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