DBMS > Bangdb vs. Blueflood vs. IRONdb vs. JaguarDB vs. KairosDB

System Properties Comparison Bangdb vs. Blueflood vs. IRONdb vs. JaguarDB vs. KairosDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Scalable TimeSeries DBMS based on Cassandra

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Performant, highly scalable DBMS for AI and IoT applications

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Key-value store
Vector DBMS

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

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Website

bangdb.com

blueflood.io

www.circonus.com/solutions/time-series-database/

www.jaguardb.com

github.com/kairosdb/kairosdb

Technical documentation

docs.bangdb.com

github.com/rax-maas/blueflood/wiki

docs.circonus.com/irondb/category/getting-started

www.jaguardb.com/support.html

kairosdb.github.io

Developer

Sachin Sinha, BangDB

Rackspace

Circonus LLC.

DataJaguar, Inc.

Initial release

2012

2013

2017

2015

2013

Current release

BangDB 2.0, October 2021

V0.10.20, January 2018

3.3 July 2023

1.2.2, November 2018

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

commercial

Open Source

GPL V3.0

Open Source

Apache 2.0

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 and C++

C++

the server part. Clients available in other languages

Java

Server operating systems

Linux

Linux
OS X

Linux

Linux
OS X
Windows

Data scheme

schema-free

predefined scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

text, numeric, histograms

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

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language (Circonus Analytics Query Language: CAQL)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP REST

HTTP API

JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes, in Lua

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

Automatic, metric affinity per node

Sharding

based on Cassandra

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

configurable replication factor, datacenter aware

Multi-source replication

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

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

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)

rights management via user accounts

simple password-based access control

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