DBMS > MySQL vs. Snowflake vs. Solr vs. WakandaDB

System Properties Comparison MySQL vs. Snowflake vs. Solr vs. WakandaDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

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

A widely used distributed, scalable search engine based on Apache Lucene

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Search engine

Object oriented DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

dev.mysql.com/doc

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

wakanda.github.io/doc

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Snowflake Computing Inc.

Apache Software Foundation

Wakanda SAS

Initial release

1995

2014

2006

2012

Current release

8.4.0, April 2024

9.6.0, April 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache Version 2

Open Source

AGPLv3, extended commercial license available

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and C++

Java

C++, JavaScript

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
OS X
Windows

Data scheme

yes

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

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

yes

Solr Parallel SQL Interface

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

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

JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

yes

proprietary syntax

user defined functions

Java plugins

yes

Triggers

yes

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

ACID

optimistic locking

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

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

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

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.