DBMS > Bangdb vs. Blueflood vs. Google Cloud Bigtable vs. SiteWhere

System Properties Comparison Bangdb vs. Blueflood vs. Google Cloud Bigtable vs. SiteWhere

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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

Scalable TimeSeries DBMS based on Cassandra

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Key-value store
Wide column store

Time Series DBMS

Secondary database models

Spatial 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	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

bangdb.com

blueflood.io

cloud.google.com/bigtable

github.com/sitewhere/sitewhere

Technical documentation

docs.bangdb.com

github.com/rax-maas/blueflood/wiki

cloud.google.com/bigtable/docs

sitewhere1.sitewhere.io/index.html

Developer

Sachin Sinha, BangDB

Rackspace

Google

SiteWhere

Initial release

2012

2013

2015

2010

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

commercial

Open Source

Common Public Attribution License Version 1.0

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++

Java

Server operating systems

Linux

Linux
OS X

hosted

Linux
OS X
Windows

Data scheme

schema-free

predefined scheme

schema-free

predefined scheme

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

SQL

Support of SQL

SQL like support with command line tool

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP REST

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP REST

Supported programming languages

C
C#
C++
Java
Python

C#
C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

yes, Notifications (with Streaming only)

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

based on Cassandra

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

based on Cassandra

Internal replication in Colossus, and regional replication between two clusters in different zones

selectable replication factor

based on HBase

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic single-row operations

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

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

User concepts

Access control

yes (enterprise version only)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Users with fine-grained authorization concept

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