DBMS > Amazon Aurora vs. Apache Spark (SQL) vs. SQLite

System Properties Comparison Amazon Aurora vs. Apache Spark (SQL) vs. SQLite

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

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

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Secondary database models

Document store

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

Score	7.48
Rank	#45	Overall
	#28	Relational DBMS

Score	17.39
Rank	#32	Overall
	#20	Relational DBMS

Score	101.72
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/rds/aurora

spark.apache.org/sql

www.sqlite.org

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

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

www.sqlite.org/docs.html

Developer

Amazon

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2015

2014

2000

Current release

3.5.0 ( 2.13), September 2023

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Public Domain

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

Scala

Server operating systems

hosted

Linux
OS X
Windows

server-less

Data scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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

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

fine grained access rights according to SQL-standard

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

Big gains for Relational Database Management Systems in DB-Engines Ranking
2 February 2016, Matthias Gelbmann

show all

Recent citations in the news

Introducing Amazon Aurora DSQL | Amazon Web Services
3 December 2024, AWS Blog

New Amazon CloudWatch Database Insights: Comprehensive database observability from fleets to instances
1 December 2024, AWS Blog

AWS announces Aurora DSQL, a new distributed SQL database that promises virtually unlimited scalability
3 December 2024, TechCrunch

AWS Announces New Database Capabilities Including Amazon Aurora DSQL, the Fastest Distributed SQL Database
3 December 2024, Business Wire

AWS introduces Amazon Aurora DSQL and DynamoDB enhancements for multi-region workloads
3 December 2024, SiliconANGLE News

provided by Google News

Introducing generative AI upgrades for Apache Spark in AWS Glue (preview)
22 November 2024, AWS Blog

Top 80+ Apache Spark Interview Questions and Answers for 2025
12 November 2024, Simplilearn

Introducing generative AI troubleshooting for Apache Spark in AWS Glue (preview)
22 November 2024, AWS Blog

Sparkle: Standardizing Modular ETL at Uber
15 August 2024, Uber

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

provided by Google News

Zero-latency SQLite storage in every Durable Object
26 September 2024, The Cloudflare Blog

How to install SQLite on Windows
20 October 2024, TheServerSide.com

Optimize Your SQLite Database with the Laravel Optimize DB Package
6 October 2024, Laravel News

Ruby on Rails 8.0 first beta release: A big bet on SQLite in production
9 October 2024, DevClass

Google’s AI Tool Big Sleep Finds Zero-Day Vulnerability in SQLite Database Engine
4 November 2024, The Hacker News

provided by Google News

Share this page