DBMS > Amazon Aurora vs. Apache IoTDB vs. H2 vs. Oracle vs. TimescaleDB

System Properties Comparison Amazon Aurora vs. Apache IoTDB vs. H2 vs. Oracle vs. TimescaleDB

Editorial information provided by DB-Engines

Name

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Widely used RDBMS

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Document store

Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Relational DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

aws.amazon.com/rds/aurora

iotdb.apache.org

www.h2database.com

www.oracle.com/database

www.timescale.com

Technical documentation

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

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

www.h2database.com/html/main.html

docs.oracle.com/en/database

docs.timescale.com

Developer

Amazon

Apache Software Foundation

Thomas Mueller

Oracle

Timescale

Initial release

2015

2018

2005

1980

2017

Current release

1.1.0, April 2023

2.2.220, July 2023

23c, September 2023

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

restricted free version is available

Open Source

Apache 2.0

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++

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Windows

Data scheme

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

with proprietary extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
Native API

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

Java

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

PL/SQL

also stored procedures in Java possible

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

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

none

Sharding, horizontal partitioning

yes, across time and space (hash partitioning) attributes

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

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

can be realized in PL/SQL

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

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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