DBMS > Apache IoTDB vs. Cachelot.io vs. SAP IQ vs. Yanza

System Properties Comparison Apache IoTDB vs. Cachelot.io vs. SAP IQ vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

In-memory caching system

Columnar RDBMS optimized for Big Data analytics

Time Series DBMS for IoT Applications

Primary database model

column-oriented

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	2.56
Rank	#106	Overall
	#52	Relational DBMS

Website

iotdb.apache.org

cachelot.io

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

yanza.com

Technical documentation

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

help.sap.com/docs/SAP_IQ

Developer

Apache Software Foundation

SAP, formerly Sybase

Yanza

Initial release

2018

2015

1994

2015

Current release

1.1.0, April 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Simplified BSD License

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
OS X

AIX
HP-UX
Linux
Solaris
Windows

Windows

Data scheme

yes

schema-free

yes

schema-free

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

yes

APIs and other access methods

JDBC
Native API

Memcached protocol

ADO.NET
JDBC
ODBC
RESTful HTTP API

HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Ruby

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

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

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

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

none

SAP/Sybase Replication Server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

none

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

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

User concepts

Access control

yes

fine grained access rights according to SQL-standard

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