DBMS > Apache IoTDB vs. InfluxDB vs. SAP Adaptive Server vs. SQLite vs. Tibero

System Properties Comparison Apache IoTDB vs. InfluxDB vs. SAP Adaptive Server vs. SQLite vs. Tibero

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

DBMS for storing time series, events and metrics

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Widely used embeddable, in-process RDBMS

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

iotdb.apache.org

www.influxdata.com/products/influxdb-overview

www.sap.com/products/technology-platform/sybase-ase.html

www.sqlite.org

us.tmaxsoft.com/products/tibero

Technical documentation

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

docs.influxdata.com/influxdb

help.sap.com/docs/SAP_ASE

www.sqlite.org/docs.html

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Apache Software Foundation

SAP, Sybase

Dwayne Richard Hipp

TmaxSoft

Initial release

2018

2013

1987

2000

2003

Current release

1.1.0, April 2023

2.7.6, April 2024

16.0

3.45.3 (15 April 2024), April 2024

6, April 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

Public Domain

commercial

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

C and C++

C and Assembler

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X

through Homebrew

AIX
HP-UX
Linux
Solaris
Unix
Windows

server-less

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC
Native API

HTTP API
JSON over UDP

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

C
C++
Cobol
Java
Java
Perl
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

Java and Transact-SQL

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

in enterprise version only

horizontal partitioning

none

horizontal partitioning

by range, hash, list or composite

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

selectable replication factor

in enterprise version only

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

planned for next version

User concepts

Access control

yes

simple rights management via user accounts

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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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