DBMS > HugeGraph vs. InfluxDB vs. Newts vs. Riak TS vs. Tkrzw

System Properties Comparison HugeGraph vs. InfluxDB vs. Newts vs. Riak TS vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

DBMS for storing time series, events and metrics

Time Series DBMS based on Cassandra

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Graph DBMS

Time Series DBMS

Key-value store

Secondary database models

Spatial DBMS

with GEO package

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	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

github.com/hugegraph
hugegraph.apache.org

www.influxdata.com/products/influxdb-overview

opennms.github.io/newts

dbmx.net/tkrzw

Technical documentation

hugegraph.apache.org/docs

docs.influxdata.com/influxdb

github.com/OpenNMS/newts/wiki

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

Developer

Baidu

OpenNMS Group

Open Source, formerly Basho Technologies

Mikio Hirabayashi

Initial release

2018

2013

2014

2015

2020

Current release

0.9

2.7.6, April 2024

3.0.0, September 2022

0.9.3, 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 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

C++

Server operating systems

Linux
macOS
Unix

Linux
OS X

through Homebrew

Linux
OS X
Windows

Linux
OS X

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

restricted

SQL

Support of SQL

SQL-like query language

yes, limited

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API
JSON over UDP

HTTP REST
Java API

HTTP API
Native Erlang Interface

Supported programming languages

Groovy
Java
Python

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

Java

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
Ruby

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

in enterprise version only

Sharding

based on Cassandra

Sharding

none

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

selectable replication factor

based on Cassandra

selectable replication factor

none

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

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

links between datasets 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

Depending on used storage engine

yes

using specific database classes

User concepts

Access control

Users, roles and permissions

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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