DBMS > Apache IoTDB vs. Hyprcubd vs. MySQL vs. OpenTSDB vs. SAP HANA

System Properties Comparison Apache IoTDB vs. Hyprcubd vs. MySQL vs. OpenTSDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

Hyprcubd 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

Serverless Time Series DBMS

Widely used open source RDBMS

Scalable Time Series DBMS based on HBase

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

Primary database model

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

iotdb.apache.org

hyprcubd.com (offline)

www.mysql.com

opentsdb.net

www.sap.com/products/hana.html

Technical documentation

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

dev.mysql.com/doc

opentsdb.net/docs/build/html/index.html

help.sap.com/hana

Developer

Apache Software Foundation

Hyprcubd, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

currently maintained by Yahoo and other contributors

SAP

Initial release

2018

1995

2011

2010

Current release

1.1.0, April 2023

8.4.0, April 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

LGPL

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

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Implementation language

Java

C and C++

Java

Server operating systems

All OS with a Java VM (>= 1.8)

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Appliance or cloud-service

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

numeric data for metrics, strings for tags

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

yes

APIs and other access methods

JDBC
Native API

gRPC (https)

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Telnet API

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

based on HBase

yes

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

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

yes

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

Eventual Consistency

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

token access

Users with fine-grained authorization concept

no user groups or roles

yes

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