DBMS > Elasticsearch vs. MySQL vs. PlanetScale vs. Quasardb

System Properties Comparison Elasticsearch vs. MySQL vs. PlanetScale vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Widely used open source RDBMS

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Distributed, high-performance timeseries database

Primary database model

Search engine

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Spatial DBMS

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

Score	128.79
Rank	#8	Overall
	#1	Search engines

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	1.09
Rank	#178	Overall
	#82	Relational DBMS

Score	0.13
Rank	#332	Overall
	#28	Time Series DBMS

Website

www.elastic.co/elasticsearch

www.mysql.com

planetscale.com

quasar.ai

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

dev.mysql.com/doc

planetscale.com/docs

doc.quasar.ai/master

Developer

Elastic

Oracle

since 2010, originally MySQL AB, then Sun

PlanetScale

quasardb

Initial release

2010

1995

2020

2009

Current release

8.6, January 2023

9.0.0, July 2024

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Elastic License

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

C and C++

C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS

BSD
Linux
OS X
Windows

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

yes

with tags

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP API

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

proprietary syntax

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

Memcached and Redis integration

yes

Transient mode

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Users with fine-grained authorization concept

no user groups or roles

Cryptographically strong user authentication and audit trail

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