DBMS > Bangdb vs. HyperSQL vs. IRONdb vs. Percona Server for MongoDB

System Properties Comparison Bangdb vs. HyperSQL vs. IRONdb vs. Percona Server for MongoDB

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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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Document store

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	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Website

bangdb.com

hsqldb.org

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

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

docs.bangdb.com

hsqldb.org/web/hsqlDocsFrame.html

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

docs.percona.com/percona-distribution-for-mongodb

Developer

Sachin Sinha, BangDB

Circonus LLC.

Percona

Initial release

2012

2001

2017

2015

Current release

BangDB 2.0, October 2021

2.7.2, June 2023

V0.10.20, January 2018

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

BSD 3

Open Source

based on BSD license

commercial

Open Source

GPL Version 2

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++

Java

C and C++

C++

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux

Data 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

yes

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

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP API

proprietary protocol using JSON

Supported programming languages

C
C#
C++
Java
Python

All languages supporting JDBC/ODBC
Java

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

Java, SQL

yes, in Lua

JavaScript

Triggers

yes, Notifications (with Streaming only)

yes

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

none

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)

none

configurable replication factor, datacenter aware

Source-replica replication

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

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

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

via In-Memory Engine

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Access rights for users and roles

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