DBMS > Amazon Aurora vs. Apache IoTDB vs. Yanza

System Properties Comparison Amazon Aurora vs. Apache IoTDB vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

MySQL and PostgreSQL compatible cloud service by Amazon

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Website

aws.amazon.com/rds/aurora

iotdb.apache.org

yanza.com

Technical documentation

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

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

Developer

Amazon

Apache Software Foundation

Yanza

Initial release

2015

2018

2015

Current release

1.1.0, April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
Native API

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

C
C#
C++
Go
Java
Python
Scala

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

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

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

yes

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More resources

DB-Engines blog posts

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3 August 2015, Matthias Gelbmann

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Recent citations in the news

Baffle enables computation on encrypted Amazon RDS and Aurora data – Blocks and Files
1 May 2024, Blocks and Files

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
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18 April 2024, AWS Blog

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1 May 2024, Yahoo Finance

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8 November 2023, AWS Blog

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