DBMS > Apache IoTDB vs. Hawkular Metrics vs. Qdrant vs. Riak TS

System Properties Comparison Apache IoTDB vs. Hawkular Metrics vs. Qdrant vs. Riak TS

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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 high-performance vector database with neural network or semantic-based matching

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Time Series DBMS

Vector DBMS

Time Series 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	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

iotdb.apache.org

www.hawkular.org

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

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

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

qdrant.tech/documentation

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Apache Software Foundation

Community supported by Red Hat

Qdrant

Open Source, formerly Basho Technologies

Initial release

2018

2014

2021

2015

Current release

1.1.0, April 2023

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

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

Rust

Erlang

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

Docker
Linux
macOS
Windows

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

restricted

SQL

Support of SQL

SQL-like query language

yes, limited

APIs and other access methods

JDBC
Native API

HTTP REST

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

HTTP API
Native Erlang Interface

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Go
Java
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

via Hawkular Alerting

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

based on Cassandra

Sharding

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

Collection-level replication

selectable replication factor

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

Eventual Consistency, tunable consistency

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

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

Key-based authentication

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