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System Properties Comparison Pinecone vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

A managed, cloud-native vector database

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Vector DBMS

Key-value store

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Score	3.23
Rank	#80	Overall
	#4	Vector DBMS

Score	0.00
Rank	#391	Overall
	#62	Key-value stores

Website

www.pinecone.io

swaydb.simer.au

Technical documentation

docs.pinecone.io/docs/overview

Developer

Pinecone Systems, Inc

Simer Plaha

Initial release

2019

2018

License

Commercial or Open Source

commercial

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

Server operating systems

hosted

Data scheme

schema-free

Typing

predefined data types such as float or date

String, Number, Boolean

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

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

Supported programming languages

Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Transaction concepts

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

Atomic execution of operations

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

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Recent citations in the news

Pinecone expands vector database with cascading retrieval, boosting enterprise AI accuracy by up to 48%
2 December 2024, VentureBeat

Pinecone integrates AI inferencing with vector database
2 December 2024, Blocks and Files

Pinecone Revamps Retrieval Capabilities for Its Vector Database Platform
2 December 2024, The New Stack

Pinecone Spruces Up AI Knowledge Platform
2 December 2024, Forbes

First-of-its-kind Pinecone Knowledge Platform to Power Best-in-class Retrieval for Customers
3 December 2024, PR Newswire

provided by Google News

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