DBMS > Bangdb vs. DuckDB vs. Microsoft Azure SQL Database vs. Newts vs. Riak TS

System Properties Comparison Bangdb vs. DuckDB vs. Microsoft Azure SQL Database vs. Newts vs. Riak TS

Editorial information provided by DB-Engines

Name

Description

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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Database as a Service offering with high compatibility to Microsoft SQL Server

Time Series DBMS based on Cassandra

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
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	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

bangdb.com

duckdb.org

azure.microsoft.com/en-us/products/azure-sql/database

opennms.github.io/newts

Technical documentation

docs.bangdb.com

duckdb.org/docs

docs.microsoft.com/en-us/azure/azure-sql

github.com/OpenNMS/newts/wiki

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Sachin Sinha, BangDB

Microsoft

OpenNMS Group

Open Source, formerly Basho Technologies

Initial release

2012

2018

2010

2014

2015

Current release

BangDB 2.0, October 2021

1.0.0, June 2024

V12

3.0.0, September 2022

License

Commercial or Open Source

Open Source

BSD 3

Open Source

MIT License

commercial

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

C++

Java

Erlang

Server operating systems

Linux

server-less

hosted

Linux
OS X
Windows

Linux
OS X

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

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

yes

restricted

SQL

Support of SQL

SQL like support with command line tool

yes

yes, limited

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC

HTTP REST
Java API

HTTP API
Native Erlang Interface

Supported programming languages

C
C#
C++
Java
Python

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Transact SQL

Erlang

Triggers

yes, Notifications (with Streaming only)

yes

pre-commit hooks and post-commit hooks

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

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

yes, with always 3 replicas available

selectable replication factor

based on Cassandra

selectable replication factor

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

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, multi-version concurrency control (MVCC)

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

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