DBMS > Amazon DynamoDB vs. Infobright vs. Pinecone vs. PostgreSQL

System Properties Comparison Amazon DynamoDB vs. Infobright vs. Pinecone vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

A managed, cloud-native vector database

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

Document store
Key-value store

Relational DBMS

Vector DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	79.30
Rank	#15	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.79
Rank	#207	Overall
	#97	Relational DBMS

Score	3.57
Rank	#74	Overall
	#6	Vector DBMS

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Website

aws.amazon.com/dynamodb

ignitetech.com/softwarelibrary/infobrightdb

www.pinecone.io

www.postgresql.org

Technical documentation

docs.aws.amazon.com/dynamodb

docs.pinecone.io/docs/overview

www.postgresql.org/docs

Developer

Amazon

Ignite Technologies Inc.; formerly InfoBright Inc.

Pinecone Systems, Inc

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2012

2005

2019

1989

1989: Postgres, 1996: PostgreSQL

Current release

16.4, August 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

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

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Server operating systems

hosted

Linux
Windows

hosted

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

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

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

standard with numerous extensions

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

RESTful HTTP API

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

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

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

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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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