DBMS > Badger vs. Microsoft Azure AI Search vs. MonetDB vs. NSDb

System Properties Comparison Badger vs. Microsoft Azure AI Search vs. MonetDB vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Search-as-a-service for web and mobile app development

A relational database management system that stores data in columns

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

Primary database model

Secondary database models

Vector DBMS

Document store
Spatial DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

github.com/dgraph-io/badger

azure.microsoft.com/en-us/services/search

www.monetdb.org

nsdb.io

Technical documentation

godoc.org/github.com/dgraph-io/badger

learn.microsoft.com/en-us/azure/search

www.monetdb.org/Documentation

nsdb.io/Architecture

Developer

DGraph Labs

Microsoft

MonetDB BV

Initial release

2017

2015

2004

2017

Current release

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 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

Java, Scala

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

SQL 2003 with some extensions

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

gRPC
HTTP REST
WebSocket

Supported programming languages

C#
Java
JavaScript
Python

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

Java
Scala

Server-side scripts

Stored procedures

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual 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

Durability

Support for making data persistent

yes

Using Apache Lucene

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

yes

using Azure authentication

fine grained access rights according to SQL-standard

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