DBMS > HugeGraph vs. InfluxDB vs. Lovefield vs. RethinkDB vs. Transwarp ArgoDB

System Properties Comparison HugeGraph vs. InfluxDB vs. Lovefield vs. RethinkDB vs. Transwarp ArgoDB

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

DBMS for storing time series, events and metrics

Embeddable relational database for web apps written in pure JavaScript

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS

Search engine

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.07
Rank	#350	Overall
	#153	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.influxdata.com/products/influxdb-overview

google.github.io/lovefield

rethinkdb.com

www.transwarp.cn/en/product/argodb

Technical documentation

hugegraph.apache.org/docs

docs.influxdata.com/influxdb

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

rethinkdb.com/docs

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Baidu

Google

The Linux Foundation

since July 2017

Transwarp

Initial release

2018

2013

2014

2009

Current release

0.9

2.7.6, April 2024

2.1.12, February 2017

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

JavaScript

C++

Server operating systems

Linux
macOS
Unix

Linux
OS X

through Homebrew

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

string, binary, float, bool, date, geometry

yes

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

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API
JSON over UDP

Supported programming languages

Groovy
Java
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

JavaScript

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

Using read-only observers

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

in enterprise version only

none

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

selectable replication factor

in enterprise version only

none

Source-replica replication

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

Transaction concepts

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

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

Depending on used storage engine

yes

using MemoryDB

User concepts

Access control

Users, roles and permissions

simple rights management via user accounts

yes

users and table-level permissions

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
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Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
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Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
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Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
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Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
» more

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We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

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