DBMS > Microsoft Azure AI Search vs. MySQL vs. ScyllaDB vs. Snowflake vs. SWC-DB

System Properties Comparison Microsoft Azure AI Search vs. MySQL vs. ScyllaDB vs. Snowflake vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

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

Widely used open source RDBMS

Cassandra and DynamoDB compatible wide column store

Cloud-based data warehousing service for structured and semi-structured data

A high performance, scalable Wide Column DBMS

Primary database model

Search engine

Relational DBMS

Key/Value like access via memcached API

Wide column store

Relational DBMS

Wide column store

Secondary database models

Vector DBMS

Document store
Spatial DBMS

Key-value store

Time Series DBMS

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

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

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

www.mysql.com

www.scylladb.com

www.snowflake.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

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

dev.mysql.com/doc

docs.scylladb.com

docs.snowflake.net/manuals/index.html

Developer

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

ScyllaDB

Snowflake Computing Inc.

Alex Kashirin

Initial release

2015

1995

2015

2014

2020

Current release

8.4.0, April 2024

ScyllaDB Open Source 5.4.1, January 2024

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Open Source (AGPL), commercial license available

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

hosted

Linux

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

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.

yes

Secondary indexes

yes

cluster global secondary indices

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements (CQL)

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

CLI Client
JDBC
ODBC

Proprietary protocol
Thrift

Supported programming languages

C#
Java
JavaScript
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

JavaScript (Node.js)
Python

C++

Server-side scripts

Stored procedures

yes

proprietary syntax

yes, Lua

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

in-memory tables

User concepts

Access control

yes

using Azure authentication

Users with fine-grained authorization concept

no user groups or roles

Access rights for users can be defined per object

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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