DBMS > Apache IoTDB vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. Transwarp ArgoDB

System Properties Comparison Apache IoTDB vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. Transwarp ArgoDB

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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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A Wide Column Store for rapid development using massive semi-structured datasets

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Time Series DBMS

Wide column store

Relational DBMS

Secondary database models

Search engine

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Score	0.04
Rank	#361	Overall
	#153	Relational DBMS

Website

iotdb.apache.org

www.hawkular.org

azure.microsoft.com/en-us/services/storage/tables

www.transwarp.cn/en/product/argodb

Technical documentation

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

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Apache Software Foundation

Community supported by Red Hat

Microsoft

Transwarp

Initial release

2018

2014

2012

Current release

1.1.0, April 2023

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

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

hosted

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

yes

APIs and other access methods

JDBC
Native API

HTTP REST

RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Go
Java
Python
Ruby

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

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

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

optimistic locking

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

Access rights based on private key authentication or shared access signatures

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