DBMS > Amazon Redshift vs. HarperDB vs. Infobright vs. Microsoft Azure SQL Database vs. Trafodion

System Properties Comparison Amazon Redshift vs. HarperDB vs. Infobright vs. Microsoft Azure SQL Database vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Database as a Service offering with high compatibility to Microsoft SQL Server

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Website

aws.amazon.com/redshift

www.harperdb.io

ignitetech.com/softwarelibrary/infobrightdb

azure.microsoft.com/en-us/products/azure-sql/database

trafodion.apache.org

Technical documentation

docs.aws.amazon.com/redshift

docs.harperdb.io/docs

docs.microsoft.com/en-us/azure/azure-sql

trafodion.apache.org/documentation.html

Developer

Amazon (based on PostgreSQL)

HarperDB

Ignite Technologies Inc.; formerly InfoBright Inc.

Microsoft

Apache Software Foundation, originally developed by HP

Initial release

2012

2017

2005

2010

2014

Current release

3.1, August 2021

V12

2.3.0, February 2019

License

Commercial or Open Source

commercial

free community edition available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

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

Node.js

C++

C++, Java

Server operating systems

hosted

Linux
OS X

Linux
Windows

hosted

Linux

Data scheme

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

restricted

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like data manipulation statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.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
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

in Python

Custom Functions

since release 3.1

Transact SQL

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

Source-replica replication

yes, with always 3 replicas available

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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