DBMS > Apache IoTDB vs. Drizzle vs. Hawkular Metrics vs. OpenMLDB vs. Transwarp StellarDB

System Properties Comparison Apache IoTDB vs. Drizzle vs. Hawkular Metrics vs. OpenMLDB vs. Transwarp StellarDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle 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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

An open-source machine learning database that provides a feature platform for training and inference

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Secondary database models

Relational DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Website

iotdb.apache.org

www.hawkular.org

openmldb.ai

www.transwarp.cn/en/product/stellardb

Technical documentation

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

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

openmldb.ai/docs/zh/main

Developer

Apache Software Foundation

Drizzle project, originally started by Brian Aker

Community supported by Red Hat

4 Paradigm Inc.

Transwarp

Initial release

2018

2008

2014

2020

Current release

1.1.0, April 2023

7.2.4, September 2012

2024-2 February 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

commercial

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++

Java

C++, Java, Scala

Server operating systems

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
OS X

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

Fixed schema

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

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

JDBC
Native API

JDBC

HTTP REST

JDBC
SQLAlchemy

OpenCypher

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C++
Java
PHP

Go
Java
Python
Ruby

C++
Go
Java
Python
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

hooks for callbacks inside the server can be used.

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

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

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

yes

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More resources

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