DBMS > Amazon Aurora vs. HarperDB vs. InfluxDB vs. Ingres vs. MySQL

System Properties Comparison Amazon Aurora vs. HarperDB vs. InfluxDB vs. Ingres vs. MySQL

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

DBMS for storing time series, events and metrics

Well established RDBMS

Widely used open source RDBMS

Primary database model

Key/Value like access via memcached API

Secondary database models

Document store

Spatial DBMS

with GEO package

Document store
Spatial DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

aws.amazon.com/rds/aurora

www.harperdb.io

www.influxdata.com/products/influxdb-overview

www.actian.com/databases/ingres

www.mysql.com

Technical documentation

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

docs.harperdb.io/docs

docs.influxdata.com/influxdb

docs.actian.com/ingres

dev.mysql.com/doc

Developer

Amazon

HarperDB

Actian Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2015

2017

2013

1974

originally developed at University Berkely in early 1970s

1995

Current release

3.1, August 2021

2.7.6, April 2024

11.2, May 2022

8.4.0, April 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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.

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Implementation language

Node.js

C and C++

Server operating systems

hosted

Linux
OS X

through Homebrew

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

Numeric data and Strings

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

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like data manipulation statements

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

HTTP API
JSON over UDP

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC
Proprietary native 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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

A table resides as a whole on one (or more) nodes in a cluster

Sharding

in enterprise version only

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

the nodes on which a table resides can be defined

selectable replication factor

in enterprise version only

Ingres Replicator

Multi-source replication
Source-replica replication

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

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on used storage engine

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

simple rights management via user accounts

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.