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

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

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Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Website

github.com/boltdb/bolt

github.com/dragonflydb/dragonfly
www.dragonflydb.io

cloud.google.com/bigquery

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

Technical documentation

www.dragonflydb.io/docs

cloud.google.com/bigquery/docs

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

Developer

DragonflyDB team and community contributors

Google

Microsoft

Initial release

2013

2023

2010

2015

Current release

1.0, March 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

BSL 1.1

commercial

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++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

hosted

Data scheme

schema-free

scheme-free

yes

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

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

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

Lua

user defined functions

in JavaScript

Triggers

publish/subscribe channels provide some trigger functionality

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

Source-replica replication

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Atomic execution of command blocks and scripts

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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.

yes

User concepts

Access control

Password-based authentication

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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