DBMS > Pinecone vs. Sequoiadb vs. ToroDB vs. VelocityDB

System Properties Comparison Pinecone vs. Sequoiadb vs. ToroDB vs. VelocityDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A managed, cloud-native vector database

NewSQL database with distributed OLTP and SQL

A MongoDB-compatible JSON document store, built on top of PostgreSQL

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Vector DBMS

Document store
Relational DBMS

Document store

Graph DBMS
Object oriented DBMS

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

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

www.pinecone.io

www.sequoiadb.com

github.com/torodb/server

velocitydb.com

Technical documentation

docs.pinecone.io/docs/overview

www.sequoiadb.com/en/index.php?m=Files&a=index

velocitydb.com/UserGuide

Developer

Pinecone Systems, Inc

Sequoiadb Ltd.

8Kdata

VelocityDB Inc

Initial release

2019

2013

2016

2011

Current release

7.x

License

Commercial or Open Source

commercial

Open Source

Server: AGPL; Client: Apache V2

Open Source

AGPL-V3

commercial

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++

Java

Server operating systems

hosted

Linux

All OS with a Java 7 VM

Any that supports .NET

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

String, Number, Boolean

yes

oid, date, timestamp, binary, regex

yes

string, integer, double, boolean, date, object_id

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

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

RESTful HTTP API

proprietary protocol using JSON

.Net

Supported programming languages

Python

.Net
C++
Java
PHP
Python

.Net

Server-side scripts

Stored procedures

JavaScript

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Document is locked during a transaction

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

simple password-based access control

Access rights for users and roles

Based on Windows Authentication

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

Pinecone Brings Serverless To Vector Databases
16 January 2024, Forbes

Pinecone: New vector database architecture a 'breakthrough' to curb AI hallucinations
16 January 2024, VentureBeat

Reimagining Vector Databases for the Generative AI Era with Pinecone Serverless on AWS | Amazon Web Services
21 March 2024, AWS Blog

Seven Vector Database Startups Poised to Win in the AI Revolution
19 April 2024, Business Insider

provided by Google News

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