DBMS > InfluxDB vs. LeanXcale vs. mSQL vs. OrigoDB vs. RDF4J

System Properties Comparison InfluxDB vs. LeanXcale vs. mSQL vs. OrigoDB vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

DBMS for storing time series, events and metrics

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

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

Primary database model

Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

Document store
Object oriented DBMS

RDF store

Secondary database models

Spatial DBMS

with GEO package

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

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.35
Rank	#283	Overall
	#41	Key-value stores
	#128	Relational DBMS

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

www.influxdata.com/products/influxdb-overview

www.leanxcale.com

hughestech.com.au/products/msql

origodb.com

rdf4j.org

Technical documentation

docs.influxdata.com/influxdb

origodb.com/docs

rdf4j.org/documentation

Developer

LeanXcale

Hughes Technologies

Robert Friberg et al

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

Initial release

2013

2015

1994

2009

under the name LiveDB

2004

Current release

2.7.5, January 2024

4.4, October 2021

License

Commercial or Open Source

Open Source

MIT-License; commercial enterprise version available

commercial

free licenses can be provided

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Server operating systems

Linux
OS X

through Homebrew

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

Numeric data and Strings

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

through Apache Derby

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

HTTP API
JSON over UDP

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC

.NET Client API
HTTP API
LINQ

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

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

C
Java
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

none

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

in-memory storage is supported as well

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

User concepts

Access control

simple rights management via user accounts

Role based authorization

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...
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News

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26 March 2024

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

Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services
14 March 2024, AWS Blog

Amazon Timestream: Managed InfluxDB for Time Series Data
14 March 2024, The New Stack

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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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