DBMS > HugeGraph vs. Pinecone vs. Riak KV

System Properties Comparison HugeGraph vs. Pinecone vs. Riak KV

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

A managed, cloud-native vector database

Distributed, fault tolerant key-value store

Primary database model

Graph DBMS

Vector DBMS

Key-value store

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

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

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

Website

github.com/hugegraph
hugegraph.apache.org

www.pinecone.io

Technical documentation

hugegraph.apache.org/docs

docs.pinecone.io/docs/overview

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

Developer

Baidu

Pinecone Systems, Inc

OpenSource, formerly Basho Technologies

Initial release

2018

2019

2009

Current release

0.9

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java

Erlang

Server operating systems

Linux
macOS
Unix

hosted

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

also supports composite index and range index

restricted

SQL

Support of SQL

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

Groovy
Java
Python

Python

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

asynchronous Gremlin script jobs

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

links between data sets can be stored

Transaction concepts

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

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

Users, roles and permissions

yes, using Riak Security

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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

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
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13 January 2015, Data Center Knowledge

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12 September 2017, ComputerWeekly.com

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28 November 2013, DatacenterDynamics

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