DBMS > Percona Server for MySQL vs. PouchDB vs. Spark SQL vs. SQLite vs. XTDB

System Properties Comparison Percona Server for MySQL vs. PouchDB vs. Spark SQL vs. SQLite vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

JavaScript DBMS with an API inspired by CouchDB

Spark SQL is a component on top of 'Spark Core' for structured data processing

Widely used embeddable, in-process RDBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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Trend Chart

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.percona.com/software/mysql-database/percona-server

pouchdb.com

spark.apache.org/sql

www.sqlite.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.percona.com/downloads/Percona-Server-LATEST

pouchdb.com/guides

spark.apache.org/docs/latest/sql-programming-guide.html

www.sqlite.org/docs.html

www.xtdb.com/docs

Developer

Percona

Apache Software Foundation

Dwayne Richard Hipp

Juxt Ltd.

Initial release

2008

2012

2014

2000

2019

Current release

8.0.36-28, 2024

7.1.1, June 2019

3.5.0 ( 2.13), September 2023

3.45.3 (15 April 2024), April 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

GPL version 2

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

JavaScript

Scala

Clojure

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

server-less

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes, extensible-data-notation format

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

via views

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

HTTP REST
JDBC

Supported programming languages

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript

Java
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Clojure
Java

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication
XtraDB Cluster

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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