DBMS > Bangdb vs. OrigoDB vs. SiteWhere vs. SWC-DB

System Properties Comparison Bangdb vs. OrigoDB vs. SiteWhere vs. SWC-DB

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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

A fully ACID in-memory object graph database

M2M integration platform for persisting/querying time series data

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store
Object oriented DBMS

Time Series DBMS

Wide column store

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	#380	Overall
	#50	Document stores
	#19	Object oriented DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

bangdb.com

origodb.com

github.com/sitewhere/sitewhere

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.bangdb.com

origodb.com/docs

sitewhere1.sitewhere.io/index.html

Developer

Sachin Sinha, BangDB

Robert Friberg et al

SiteWhere

Alex Kashirin

Initial release

2012

2009

under the name LiveDB

2010

2020

Current release

BangDB 2.0, October 2021

0.5, April 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Common Public Attribution License Version 1.0

Open Source

GPL V3

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++

Java

C++

Server operating systems

Linux

Linux
Windows

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

predefined scheme

schema-free

Typing

predefined data types such as float or date

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

User defined using .NET types and collections

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.

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

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

.NET Client API
HTTP API
LINQ

HTTP REST

Proprietary protocol
Thrift

Supported programming languages

C
C#
C++
Java
Python

.Net

C++

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

horizontal partitioning

client side managed; servers are not synchronized

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

selectable replication factor

based on HBase

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

Immediate Consistency

Foreign keys

Referential integrity

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

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)

Role based authorization

Users with fine-grained authorization concept

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