DBMS > Bangdb vs. Microsoft Azure SQL Database vs. Newts vs. YugabyteDB

System Properties Comparison Bangdb vs. Microsoft Azure SQL Database vs. Newts vs. YugabyteDB

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Editorial information provided by DB-Engines

Name

Description

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

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

Time Series DBMS based on Cassandra

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Wide column store

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

Score	0.07
Rank	#347	Overall
	#48	Document stores
	#36	Graph DBMS
	#31	Time Series DBMS

Score	76.53
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#386	Overall
	#41	Time Series DBMS

Score	2.36
Rank	#107	Overall
	#53	Relational DBMS

Website

bangdb.com

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

opennms.github.io/newts

www.yugabyte.com

Technical documentation

docs.bangdb.com

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

github.com/OpenNMS/newts/wiki

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Sachin Sinha, BangDB

Microsoft

OpenNMS Group

Yugabyte Inc.

Initial release

2012

2010

2014

2017

Current release

BangDB 2.0, October 2021

V12

2.19, September 2023

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

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

C and C++

Server operating systems

Linux

hosted

Linux
OS X
Windows

Linux
OS X

Data scheme

schema-free

yes

schema-free

depending on used data model

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

SQL

Support of SQL

SQL like support with command line tool

yes

yes, PostgreSQL compatible

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP REST
Java API

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

C
C#
C++
Java
Python

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

Java

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala

Server-side scripts

Stored procedures

Transact SQL

yes

sql, plpgsql, C

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

based on Cassandra

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes, with always 3 replicas available

selectable replication factor

based on Cassandra

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

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

based on RocksDB

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

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

yes

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More resources

DB-Engines blog posts

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7 February 2017, Matthias Gelbmann

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