DBMS > Bangdb vs. Firebase Realtime Database vs. LokiJS vs. MarkLogic vs. searchxml

System Properties Comparison Bangdb vs. Firebase Realtime Database vs. LokiJS vs. MarkLogic vs. searchxml

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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

In-memory JavaScript DBMS

Operational and transactional Enterprise NoSQL database

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Native XML DBMS
Search engine

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

bangdb.com

firebase.google.com/products/realtime-database

github.com/techfort/LokiJS

www.marklogic.com

www.searchxml.net/category/products

Technical documentation

docs.bangdb.com

firebase.google.com/docs/database

techfort.github.io/LokiJS

docs.marklogic.com

www.searchxml.net/support/handouts

Developer

Sachin Sinha, BangDB

Google

acquired by Google 2014

MarkLogic Corp.

informationpartners gmbh

Initial release

2012

2014

2001

2015

Current release

BangDB 2.0, October 2021

11.0, December 2022

1.0

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

commercial

restricted free version is available

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

C, C++

JavaScript

C++

Server operating systems

Linux

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

Windows

Data scheme

schema-free

Schema can be enforced

schema-free

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

via views

yes

SQL

Support of SQL

SQL like support with command line tool

yes

SQL92

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

JavaScript API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C
C#
C++
Java
Python

Java
JavaScript
Objective-C

JavaScript

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

limited functionality with using 'rules'

View functions in JavaScript

yes

via XQuery or JavaScript

yes

on the application server

Triggers

yes, Notifications (with Streaming only)

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

atomic operations within a single collection possible

ACID

can act as a resource manager in an XA/JTA transaction

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

yes, with Range Indexes

User concepts

Access control

yes (enterprise version only)

yes, based on authentication and database rules

Role-based access control at the document and subdocument levels

Domain, group and role-based access control at the document level and for application services

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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