DBMS > Amazon Neptune vs. Pinecone vs. Sequoiadb

System Properties Comparison Amazon Neptune vs. Pinecone vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

A managed, cloud-native vector database

NewSQL database with distributed OLTP and SQL

Primary database model

Graph DBMS
RDF store

Vector DBMS

Document store
Relational DBMS

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

Score	2.13
Rank	#111	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	3.57
Rank	#74	Overall
	#6	Vector DBMS

Score	0.32
Rank	#272	Overall
	#43	Document stores
	#125	Relational DBMS

Website

aws.amazon.com/neptune

www.pinecone.io

www.sequoiadb.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.pinecone.io/docs/overview

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

Developer

Amazon

Pinecone Systems, Inc

Sequoiadb Ltd.

Initial release

2017

2019

2013

License

Commercial or Open Source

commercial

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

C++

Server operating systems

hosted

Linux

Data scheme

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

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

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

Relationships in graphs

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

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

User concepts

Access control

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

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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