DBMS > Apache IoTDB vs. Coveo vs. InfluxDB vs. Oracle

System Properties Comparison Apache IoTDB vs. Coveo vs. InfluxDB vs. Oracle

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Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

DBMS for storing time series, events and metrics

Widely used RDBMS

Primary database model

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	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	2.28
Rank	#114	Overall
	#11	Search engines

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

iotdb.apache.org

www.coveo.com

www.influxdata.com/products/influxdb-overview

www.oracle.com/database

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.coveo.com

docs.influxdata.com/influxdb

docs.oracle.com/en/database

Developer

Apache Software Foundation

Coveo

Oracle

Initial release

2018

2012

2013

1980

Current release

1.1.0, April 2023

2.7.6, April 2024

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

hosted

Linux
OS X

through Homebrew

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

Data scheme

yes

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

schema-free

yes

Schemaless in JSON and XML columns

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC
Native API

RESTful HTTP API

HTTP API
JSON over UDP

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C#
Java
JavaScript
Python

.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

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

yes

Sharding

in enterprise version only

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

selectable replication factor

in enterprise version only

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

yes

granular access controls, API key management, content filters

simple rights management via user accounts

fine grained access rights according to SQL-standard

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

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
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Licensing and pricing models

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