DBMS > BoltDB vs. Google BigQuery vs. Microsoft Azure AI Search

System Properties Comparison BoltDB vs. Google BigQuery vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Large scale data warehouse service with append-only tables

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

Primary database model

Key-value store

Relational DBMS

Search engine

Secondary database models

Vector DBMS

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

Score	0.76
Rank	#224	Overall
	#32	Key-value stores

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	5.71
Rank	#64	Overall
	#8	Search engines

Website

github.com/boltdb/bolt

cloud.google.com/bigquery

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

Technical documentation

cloud.google.com/bigquery/docs

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

Developer

Google

Microsoft

Initial release

2013

2010

2015

Current release

License

Commercial or Open Source

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

using Azure authentication

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