DBMS > Apache IoTDB vs. Hawkular Metrics vs. Postgres-XL vs. ReductStore

System Properties Comparison Apache IoTDB vs. Hawkular Metrics vs. Postgres-XL vs. ReductStore

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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.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
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	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

iotdb.apache.org

www.hawkular.org

www.postgres-xl.org

github.com/reductstore
www.reduct.store

Technical documentation

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

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

www.postgres-xl.org/documentation

www.reduct.store/docs

Developer

Apache Software Foundation

Community supported by Red Hat

ReductStore LLC

Initial release

2018

2014

since 2012, originally named StormDB

2023

Current release

1.1.0, April 2023

10 R1, October 2018

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Mozilla public license

Open Source

Business Source License 1.1

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

C++, Rust

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

Linux
macOS

Docker
Linux
macOS
Windows

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

JDBC
Native API

HTTP REST

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Go
Java
Python
Ruby

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

based on Cassandra

horizontal partitioning

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

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

yes

Transaction concepts

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

ACID

MVCC

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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