DBMS > HugeGraph vs. Lovefield vs. Riak KV vs. Transwarp Hippo

System Properties Comparison HugeGraph vs. Lovefield vs. Riak KV vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Embeddable relational database for web apps written in pure JavaScript

Distributed, fault tolerant key-value store

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Graph DBMS

Relational DBMS

Key-value store

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

Vector DBMS

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Website

github.com/hugegraph
hugegraph.apache.org

google.github.io/lovefield

www.transwarp.cn/en/subproduct/hippo

Technical documentation

hugegraph.apache.org/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

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

Developer

Baidu

Google

OpenSource, formerly Basho Technologies

Initial release

2018

2014

2009

2023

Current release

0.9

2.1.12, February 2017

3.2.0, December 2022

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

Erlang

C++

Server operating systems

Linux
macOS
Unix

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

yes

restricted

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API
Native Erlang Interface

RESTful HTTP API

Supported programming languages

Groovy
Java
Python

JavaScript

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

C++
Java
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Erlang

Triggers

Using read-only observers

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

none

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

none

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

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Users, roles and permissions

yes, using Riak Security

Role based access control and fine grained access rights

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More resources

Recent citations in the news

POC exploit code published for 9.8-rated Apache HugeGraph RCE flaw
7 June 2024, The Register

PoC Exploit Released for High Severity Apache HugeGraph RCE flaw
7 June 2024, CybersecurityNews

AI, Lockbit, Veeam, Club Penguin, Kali, Commando Cat, HugeGraph, Aaran Leyland… – SWN #391
7 June 2024, SC Media

Microsoft's Recall criticized for security shortcomings. Cyberespionage in Ukraine.
11 June 2024, The CyberWire

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

provided by Google News

Basho Revamps Riak Open-Source Database
22 September 2023, InformationWeek

A Critique of Resizable Hash Tables: Riak Core & Random Slicing
26 August 2018, InfoQ.com

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

Basho to Bolster Riak with DB Plug-Ins
5 May 2014, Datanami

Basho Advances NoSQL Riak Enterprise 2.0 With Search, Advanced Data Types
15 September 2014, Data Center Knowledge

provided by Google News

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