DBMS > InfluxDB vs. Machbase Neo vs. RDF4J vs. Riak TS vs. Sequoiadb

System Properties Comparison InfluxDB vs. Machbase Neo vs. RDF4J vs. Riak TS vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

DBMS for storing time series, events and metrics

TimeSeries DBMS for AIoT and BigData

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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

NewSQL database with distributed OLTP and SQL

Primary database model

Time Series DBMS

RDF store

Time Series DBMS

Document store
Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.influxdata.com/products/influxdb-overview

machbase.com

rdf4j.org

www.sequoiadb.com

Technical documentation

docs.influxdata.com/influxdb

machbase.com/dbms

rdf4j.org/documentation

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

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Machbase

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Open Source, formerly Basho Technologies

Sequoiadb Ltd.

Initial release

2013

2004

2015

2013

Current release

2.7.6, April 2024

V8.0, August 2023

3.0.0, September 2022

License

Commercial or Open Source

Open Source

MIT-License; commercial enterprise version available

commercial

free test version available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Server: AGPL; Client: Apache V2

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

Erlang

C++

Server operating systems

Linux
OS X

through Homebrew

Linux
macOS
Windows

Linux
OS X
Unix
Windows

Linux
OS X

Linux

Data scheme

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

Numeric data and Strings

yes

oid, date, timestamp, binary, regex

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

restricted

yes

SQL

Support of SQL

SQL-like query language

yes, limited

SQL-like query language

APIs and other access methods

HTTP API
JSON over UDP

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API
Native Erlang Interface

proprietary protocol using JSON

Supported programming languages

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Java
PHP
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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Erlang

JavaScript

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

selectable replication factor

none

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

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

ACID

Isolation support depends on the API used

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

volatile and lookup table

User concepts

Access control

simple rights management via user accounts

simple password-based access control

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

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

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

News

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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)

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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Recent citations in the news

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14 March 2024, AWS Blog

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14 March 2024, Business Wire

How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency
15 March 2024, Datanami

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5 April 2024, VentureBeat

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