DBMS > Bangdb vs. HEAVY.AI vs. IRONdb vs. JaguarDB

System Properties Comparison Bangdb vs. HEAVY.AI vs. IRONdb vs. JaguarDB

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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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Key-value store
Vector 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	1.77
Rank	#141	Overall
	#65	Relational DBMS

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

Website

bangdb.com

github.com/heavyai/heavydb
www.heavy.ai

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

www.jaguardb.com

Technical documentation

docs.bangdb.com

docs.heavy.ai

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

www.jaguardb.com/support.html

Developer

Sachin Sinha, BangDB

HEAVY.AI, Inc.

Circonus LLC.

DataJaguar, Inc.

Initial release

2012

2016

2017

2015

Current release

BangDB 2.0, October 2021

5.10, January 2022

V0.10.20, January 2018

3.3 July 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

GPL V3.0

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++ and CUDA

C and C++

C++

the server part. Clients available in other languages

Server operating systems

Linux

Data scheme

schema-free

yes

schema-free

yes

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

yes

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

JDBC
ODBC
Thrift
Vega

HTTP API

JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

All languages supporting JDBC/ODBC/Thrift
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

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

Round robin

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

configurable replication factor, datacenter aware

Multi-source 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

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

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

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

rights management via user accounts

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