DBMS > Amazon Aurora vs. Apache Pinot vs. ITTIA

System Properties Comparison Amazon Aurora vs. Apache Pinot vs. ITTIA

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Editorial information provided by DB-Engines

Name

Description

Fully managed relational database service built for the cloud providing unparalleled high performance and availability at global scale for MySQL, PostgreSQL, and DSQL

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Edge Time Series DBMS with Real-Time Stream Processing

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Relational DBMS

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

Score	7.33
Rank	#46	Overall
	#29	Relational DBMS

Score	0.46
Rank	#252	Overall
	#118	Relational DBMS

Score	0.44
Rank	#253	Overall
	#21	Time Series DBMS

Website

aws.amazon.com/rds/aurora

pinot.apache.org

www.ittia.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_AuroraOverview.html
docs.aws.amazon.com/aurora-dsql/latest/userguide/what-is-aurora-dsql.html

docs.pinot.apache.org

Social network pages

Developer

Amazon

Apache Software Foundation and contributors

ITTIA L.L.C.

Initial release

2015

2007

Current release

Aurora DSQL, November 2024 (preview), PostgreSQL: docs.aws.amazon.com/AmazonRDS/latest/AuroraPostgreSQLReleaseNotes/AuroraPostgreSQL.Updates.html , MySQL: docs.aws.amazon.com/AmazonRDS/latest/AuroraMySQLReleaseNotes/AuroraMySQL.release-calendars.html

1.0.0, September 2023

8.7

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

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

PostgreSQL/MySQL: C, C++, Aurora DSQL: Rust

Java

C and C++

Server operating systems

Amazon Linux

All OS with a Java JDK11 or higher

Linux
Windows

Data scheme

yes

Fixed schema

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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, MySQL and PostgreSQL dialects

SQL-like query language

yes

APIs and other access methods

DSQL API: docs.aws.amazon.com/aurora-dsql/latest/userguide/CHAP_api_reference.html
MySQL wire protocol
PostgreSQL wire protocol
RDS Data API: docs.aws.amazon.com/AmazonRDS/latest/UserGuide/ProgrammingGuide.html

JDBC

JDBC
ODBC
RESTful HTTP API
WebSocket

Supported programming languages

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

Go
Java
Python

C
C++
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

PL/pgSQL, MySQL stored program language, APG trusted language extensions

yes

Triggers

Aurora MySQL: Yes. Aurora PostgreSQL: Yes. Aurora DSQL: No.

Partitioning methods

Methods for storing different data on different nodes

DBMS table partitioning, Horizontal storage partitioning, Sharding, Distributed horizontal partitioning (DSQL)

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Full replication
Logical replication
Snapshot replication
Transactional replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate/Strong Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID, Multi-statement

yes

Concurrency

Support for concurrent manipulation of data

Multiversion concurrency control (MVCC) with fully compatible MySQL and PostgreSQL options. Optimistic concurrency control (OCC) in Aurora DSQL.

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

Data is replicated across 3 Availability Zones (AZs) within a single AWS Region. Active-active multi-Region high availability across 3 Regions (2 active, 1 witness) and automated failover recovery with Aurora DSQL. Automated, continuous backup of data with point in time restore. Fault-tolerant, self-healing storage system.

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

Role based permissions
Row level security

Database file passwords

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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

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Recent citations in the news

Optimizing cost savings: The advantage of Amazon Aurora over self-managed open source databases
31 March 2025, Amazon Web Services (AWS)

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Introducing Amazon Aurora DSQL | Amazon Web Services
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31 October 2024, Amazon Web Services (AWS)

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8 April 2022, Embedded Computing Design

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