DBMS > Amazon Redshift vs. Apache Impala vs. EDB Postgres vs. HarperDB

System Properties Comparison Amazon Redshift vs. Apache Impala vs. EDB Postgres vs. HarperDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for Hadoop

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

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.

Primary database model

Relational DBMS

Document store

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	1.86
Rank	#131	Overall
	#61	Relational DBMS

Score	0.55
Rank	#243	Overall
	#38	Document stores

Website

aws.amazon.com/redshift

impala.apache.org

www.enterprisedb.com

www.harperdb.io

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

www.enterprisedb.com/docs

docs.harperdb.io/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

EnterpriseDB

HarperDB

Initial release

2012

2013

2005

2017

Current release

4.1.0, June 2022

14, December 2021

3.1, August 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

BSD for PostgreSQL-components

commercial

free community edition 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.

Implementation language

C++

Node.js

Server operating systems

hosted

Linux

Linux
Windows

Linux
OS X

Data scheme

yes

dynamic schema

Typing

predefined data types such as float or date

yes

JSON 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

specific XML-type available, but no XML query functionality.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

standard with numerous extensions

SQL-like data manipulation statements

APIs and other access methods

JDBC
ODBC

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
PHP
Python
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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Custom Functions

since release 3.1

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

by hash, list or range

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication

yes

the nodes on which a table resides can be defined

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Access rights for users and roles

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