DBMS > Bangdb vs. EXASOL vs. IRONdb vs. STSdb vs. SwayDB

System Properties Comparison Bangdb vs. EXASOL vs. IRONdb vs. STSdb vs. SwayDB

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Key-value store

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.15
Rank	#334	Overall
	#45	Document stores
	#31	Graph DBMS
	#31	Time Series DBMS

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Score	0.04
Rank	#373	Overall
	#57	Key-value stores

Website

bangdb.com

www.exasol.com

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

github.com/STSSoft/STSdb4

swaydb.simer.au

Technical documentation

docs.bangdb.com

www.exasol.com/resources

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

Developer

Sachin Sinha, BangDB

Exasol

Circonus LLC.

STS Soft SC

Simer Plaha

Initial release

2012

2000

2017

2011

2018

Current release

BangDB 2.0, October 2021

V0.10.20, January 2018

4.0.8, September 2015

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

GPLv2, commercial license available

Open Source

GNU Affero GPL V3.0

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++

C and C++

Scala

Server operating systems

Linux

Windows

Data scheme

schema-free

yes

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

primitive types and user defined types (classes)

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

.Net
JDBC
ODBC
WebSocket

HTTP API

.NET Client API

Supported programming languages

C
C#
C++
Java
Python

Java
Lua
Python
R

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

C#
Java

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

yes, in Lua

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

Sharding

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

configurable replication factor, datacenter aware

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of 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

yes

User concepts

Access control

yes (enterprise version only)

Access rights for users, groups and roles according to SQL-standard

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