DBMS > Apache IoTDB vs. KairosDB vs. Kyligence Enterprise vs. SAP HANA vs. TimesTen

System Properties Comparison Apache IoTDB vs. KairosDB vs. Kyligence Enterprise vs. SAP HANA vs. TimesTen

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

Distributed Time Series DBMS based on Cassandra or H2

A distributed analytics engine for big data, built on top of Apache Kylin

In-memory, column based data store. Available as appliance or cloud service

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.60
Rank	#238	Overall
	#20	Time Series DBMS

Score	0.44
Rank	#259	Overall
	#118	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

iotdb.apache.org

github.com/kairosdb/kairosdb

kyligence.io/kyligence-enterprise

www.sap.com/products/hana.html

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

kairosdb.github.io

help.sap.com/hana

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Apache Software Foundation

Kyligence, Inc.

SAP

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2018

2013

2016

2010

1998

Current release

1.1.0, April 2023

1.2.2, November 2018

2.0 SPS07 (April 4, 2023), April 2023

Release 22.1

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

Linux

Appliance or cloud-service

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
Native API

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java
JavaScript

Node.js
PHP
Python

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

SQLScript, R

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

based on Cassandra

yes

none

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

based on Cassandra

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes

simple password-based access control

yes

fine grained access rights according to SQL-standard

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