DBMS > Pinecone vs. STSdb vs. YottaDB

System Properties Comparison Pinecone vs. STSdb vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

A managed, cloud-native vector database

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A fast and solid embedded Key-value store

Primary database model

Vector DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

www.pinecone.io

github.com/STSSoft/STSdb4

yottadb.com

Technical documentation

docs.pinecone.io/docs/overview

yottadb.com/resources/documentation

Developer

Pinecone Systems, Inc

STS Soft SC

YottaDB, LLC

Initial release

2019

2011

2001

Current release

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

GPLv2, commercial license available

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

hosted

Windows

Docker
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

String, Number, Boolean

yes

primitive types and user defined types (classes)

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

by using the Octo plugin

APIs and other access methods

RESTful HTTP API

.NET Client API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Python

C#
Java

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Foreign keys

Referential integrity

Transaction concepts

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

optimistic locking

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

Users and groups based on OS-security mechanisms

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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

PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions
11 June 2024, PR Newswire

Pinecone launches its serverless vector database out of preview
14 June 2024, Yahoo Movies UK

Pinecone’s new serverless database may see few takers, analysts say
17 January 2024, InfoWorld

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions
12 June 2024, MarkTechPost

provided by Google News

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