DBMS > Amazon Redshift vs. Apache Pinot vs. H2GIS

System Properties Comparison Amazon Redshift vs. Apache Pinot vs. H2GIS

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Spatial extension of H2

Primary database model

Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Website

aws.amazon.com/redshift

pinot.apache.org

www.h2gis.org

Technical documentation

docs.aws.amazon.com/redshift

docs.pinot.apache.org

www.h2gis.org/docs/home

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

CNRS

Initial release

2012

2015

2013

Current release

1.0.0, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

LGPL 3.0

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

Server operating systems

hosted

All OS with a Java JDK11 or higher

Data scheme

yes

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

JDBC

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
Python

Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

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

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

based on H2

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.