DBMS > InfluxDB vs. Oracle vs. ReductStore

System Properties Comparison InfluxDB vs. Oracle vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

DBMS for storing time series, events and metrics

Widely used RDBMS

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

with GEO package

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	21.54
Rank	#28	Overall
	#1	Time Series DBMS

Score	1231.05
Rank	#1	Overall
	#1	Relational DBMS

Score	0.05
Rank	#357	Overall
	#37	Time Series DBMS

Website

www.influxdata.com/products/influxdb-overview

www.oracle.com/database

github.com/reductstore
www.reduct.store

Technical documentation

docs.influxdata.com/influxdb

docs.oracle.com/en/database

www.reduct.store/docs

Developer

Oracle

ReductStore LLC

Initial release

2013

1980

2023

Current release

2.7.6, April 2024

23c, September 2023

1.9, March 2024

License

Commercial or Open Source

Open Source

MIT-License; commercial enterprise version available

commercial

restricted free version is available

Open Source

Business Source License 1.1

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

C and C++

C++, Rust

Server operating systems

Linux
OS X

through Homebrew

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Docker
Linux
macOS
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

HTTP API
JSON over UDP

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP API

Supported programming languages

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

Build a Time Series Forecasting Pipeline in InfluxDB 3 Without Writing Code
17 April 2025

InfluxDB 3 Core & Enterprise GA: The Next Generation Time Series Platform for Developers is Here
15 April 2025

Deadman Alerts with the Python Processing Engine
9 April 2025

Optimizing SQL (and DataFrames) in DataFusion: Part 2
3 April 2025

Simplifying Multi-Node Setups with InfluxDB 3 Enterprise Modes
2 April 2025

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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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

show all

MySQL is the DBMS of the Year 2019
3 January 2020, Matthias Gelbmann, Paul Andlinger

The struggle for the hegemony in Oracle's database empire
2 May 2017, Paul Andlinger

Architecting eCommerce Platforms for Zero Downtime on Black Friday and Beyond
25 November 2016, Tony Branson (guest author)

show all

Recent citations in the news

InfluxData Releases InfluxDB 3 Core and InfluxDB 3 Enterprise
16 April 2025, Database Trends and Applications

InfluxData rolls out InfluxDB 3 to power real-time apps at scale
15 April 2025, Blocks and Files

InfluxData Announces General Availability of InfluxDB 3 Core and InfluxDB 3 Enterprise, Simplifying How Developers Build with Time Series Data
15 April 2025, Business Wire

InfluxDB 3 Core & Enterprise bring high-speed data tools
17 April 2025, IT Brief Asia

Time series data: AWS/InfluxDB team up for open-source innovation
7 April 2025, SiliconANGLE

provided by Google News

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provided by Google News

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