DBMS > DataFS vs. Pinecone vs. RDF4J vs. Sequoiadb

System Properties Comparison DataFS vs. Pinecone vs. RDF4J vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

A managed, cloud-native vector database

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

NewSQL database with distributed OLTP and SQL

Primary database model

Object oriented DBMS

Vector DBMS

RDF store

Document store
Relational DBMS

Secondary database models

Graph DBMS

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

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Website

Technical documentation

dev.mobiland.com/Overview.xsp

docs.pinecone.io/docs/overview

rdf4j.org/documentation

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

Developer

Mobiland AG

Pinecone Systems, Inc

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Sequoiadb Ltd.

Initial release

2018

2019

2004

2013

Current release

1.1.263, October 2022

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Server: AGPL; Client: Apache V2

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

C++

Server operating systems

Windows

hosted

Linux
OS X
Unix
Windows

Linux

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

String, Number, Boolean

yes

oid, date, timestamp, binary, regex

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

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

proprietary protocol using JSON

Supported programming languages

.Net
C
C#
C++
VB.Net

Python

Java
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Windows-Profile

simple password-based 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

Using the Pinecone vector database in .NET
12 September 2024, InfoWorld

Pinecone serverless goes multicloud as vector database market heats up
27 August 2024, VentureBeat

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

Pinecone vector database available on AWS, Azure, and Google clouds
27 August 2024, Blocks & Files

Pinecone launches serverless vector database on Azure, GCP
27 August 2024, TechTarget

provided by Google News

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