DBMS > Pinecone vs. Postgres-XL vs. Riak KV vs. ToroDB

System Properties Comparison Pinecone vs. Postgres-XL vs. Riak KV vs. ToroDB

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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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Distributed, fault tolerant key-value store

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

Primary database model

Vector DBMS

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

www.pinecone.io

www.postgres-xl.org

github.com/torodb/server

Technical documentation

docs.pinecone.io/docs/overview

www.postgres-xl.org/documentation

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Pinecone Systems, Inc

OpenSource, formerly Basho Technologies

8Kdata

Initial release

2019

2014

since 2012, originally named StormDB

2009

2016

Current release

10 R1, October 2018

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

Apache version 2, commercial enterprise edition

Open Source

AGPL-V3

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

Erlang

Java

Server operating systems

hosted

Linux
macOS

Linux
OS X

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

String, Number, Boolean

yes

string, integer, double, boolean, date, object_id

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API
Native Erlang Interface

Supported programming languages

Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

MVCC

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.

User concepts

Access control

fine grained access rights according to SQL-standard

yes, using Riak Security

Access rights for users and roles

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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

Pinecone’s vector database gets a new serverless architecture
16 January 2024, TechCrunch

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22 September 2023, InformationWeek

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23 December 2011, InfoQ.com

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13 January 2015, Data Center Knowledge

Riak NoSQL snapped up by Bet365
12 September 2017, ComputerWeekly.com

Basho distributes Riak to more customers - DCD
28 November 2013, DatacenterDynamics

provided by Google News

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