DBMS > Adabas vs. Apache IoTDB vs. InfluxDB vs. KairosDB vs. SQLite

System Properties Comparison Adabas vs. Apache IoTDB vs. InfluxDB vs. KairosDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

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

Distributed Time Series DBMS based on Cassandra or H2

Widely used embeddable, in-process RDBMS

Primary database model

Multivalue DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

iotdb.apache.org

www.influxdata.com/products/influxdb-overview

github.com/kairosdb/kairosdb

www.sqlite.org

Technical documentation

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

docs.influxdata.com/influxdb

kairosdb.github.io

www.sqlite.org/docs.html

Developer

Software AG

Apache Software Foundation

Dwayne Richard Hipp

Initial release

1971

2018

2013

2000

Current release

1.1.0, April 2023

2.7.6, April 2024

1.2.2, November 2018

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

Open Source

Public Domain

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

BS2000
Linux
Unix
Windows
z/OS
z/VSE

All OS with a Java VM (>= 1.8)

Linux
OS X

through Homebrew

Linux
OS X
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

JDBC
Native API

HTTP API
JSON over UDP

Graphite protocol
HTTP REST
Telnet API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Natural

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

Java
JavaScript

Node.js
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

Server-side scripts

Stored procedures

in Natural

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

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

Sharding

in enterprise version only

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

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

selectable replication factor

in enterprise version only

selectable replication factor

based on Cassandra

none

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

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

yes

simple rights management via user accounts

simple password-based access control

More information provided by the system vendor

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