DBMS > Bangdb vs. JaguarDB vs. ObjectBox vs. OrigoDB

System Properties Comparison Bangdb vs. JaguarDB vs. ObjectBox vs. OrigoDB

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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

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

A fully ACID in-memory object graph database

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store
Vector DBMS

Object oriented DBMS
Vector DBMS

Document store
Object oriented DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#15	Vector DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#19	Object oriented DBMS

Website

bangdb.com

www.jaguardb.com

github.com/objectbox
objectbox.io

origodb.com

Technical documentation

docs.bangdb.com

www.jaguardb.com/support.html

docs.objectbox.io

origodb.com/docs

Developer

Sachin Sinha, BangDB

DataJaguar, Inc.

ObjectBox Limited

Robert Friberg et al

Initial release

2012

2015

2017

2009

under the name LiveDB

Current release

BangDB 2.0, October 2021

3.3 July 2023

4.0 (May 2024)

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GPL V3.0

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

C++

the server part. Clients available in other languages

C and C++

Server operating systems

Linux

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes

yes, plus "flex" map-like types

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

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

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC

Proprietary native API

.NET Client API
HTTP API
LINQ

Supported programming languages

C
C#
C++
Java
Python

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

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

Domain Events

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

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

Data sync between devices allowing occasional connected databases to work completely offline

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

Write ahead log

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

yes

Role based authorization

More information provided by the system vendor

News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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More resources

Recent citations in the news

ObjectBox Raises $2M in Funding
4 December 2018, FinSMEs

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27 August 2021, hackernoon.com

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