DBMS > Bangdb vs. IRONdb vs. NSDb vs. SAP SQL Anywhere

System Properties Comparison Bangdb vs. IRONdb vs. NSDb vs. SAP SQL Anywhere

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Relational 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	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

bangdb.com

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

nsdb.io

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.bangdb.com

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

nsdb.io/Architecture

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Sachin Sinha, BangDB

Circonus LLC.

SAP

formerly Sybase

Initial release

2012

2017

1992

Current release

BangDB 2.0, October 2021

V0.10.20, January 2018

17, July 2015

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache Version 2.0

commercial

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 C++

Java, Scala

Server operating systems

Linux

Linux
macOS

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

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: int, bigint, decimal, string

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.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

all fields are automatically indexed

yes

SQL

Support of SQL

SQL like support with command line tool

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

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP API

gRPC
HTTP REST
WebSocket

ADO.NET
HTTP API
JDBC
ODBC

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

Java
Scala

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes, in Lua

yes, in C/C++, Java, .Net or Perl

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

Automatic, metric affinity per node

Sharding

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

Source-replica replication

Database mirroring

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 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

Using Apache Lucene

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

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