DBMS > Bangdb vs. JaguarDB vs. LevelDB vs. PouchDB vs. SQLite

System Properties Comparison Bangdb vs. JaguarDB vs. LevelDB vs. PouchDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

Performant, highly scalable DBMS for AI and IoT applications

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store
Vector DBMS

Key-value store

Document store

Relational DBMS

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	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

bangdb.com

www.jaguardb.com

github.com/google/leveldb

pouchdb.com

www.sqlite.org

Technical documentation

docs.bangdb.com

www.jaguardb.com/support.html

github.com/google/leveldb/blob/main/doc/index.md

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

Sachin Sinha, BangDB

DataJaguar, Inc.

Google

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2012

2015

2011

2012

2000

Current release

BangDB 2.0, October 2021

3.3 July 2023

1.23, February 2021

7.1.1, June 2019

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GPL V3.0

Open Source

BSD

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

the server part. Clients available in other languages

C++

JavaScript

Server operating systems

Linux

Illumos
Linux
OS X
Windows

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

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

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

yes

not rigid because of 'dynamic typing' concept.

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

secondary, composite, nested, reverse, geospatial

yes

via views

yes

SQL

Support of SQL

SQL like support with command line tool

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-92 is not fully supported

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
C++
Java
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

JavaScript

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

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes, Notifications (with Streaming only)

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

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

via file-system locks

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

with automatic compression on writes

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

User concepts

Access control

yes (enterprise version only)

rights management via user accounts

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