DBMS > Drizzle vs. Hawkular Metrics vs. OpenMLDB vs. Spark SQL vs. Transwarp StellarDB

System Properties Comparison Drizzle vs. Hawkular Metrics vs. OpenMLDB vs. Spark SQL 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

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

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	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Website

www.hawkular.org

openmldb.ai

spark.apache.org/sql

www.transwarp.cn/en/product/stellardb

Technical documentation

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

openmldb.ai/docs/zh/main

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Drizzle project, originally started by Brian Aker

Community supported by Red Hat

4 Paradigm Inc.

Apache Software Foundation

Transwarp

Initial release

2008

2014

2020

2014

Current release

7.2.4, September 2012

2024-2 February 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

Apache 2.0

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

C++

Java

C++, Java, Scala

Scala

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

Fixed schema

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

yes

with proprietary extensions

yes

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC

HTTP REST

JDBC
SQLAlchemy

JDBC
ODBC

OpenCypher

Supported programming languages

C
C++
Java
PHP

Go
Java
Python
Ruby

C++
Go
Java
Python
Scala

Java
Python
R
Scala

Server-side scripts

Stored procedures

Triggers

hooks for callbacks inside the server can be used.

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

yes, utilizing Spark Core

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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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MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

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1 July 2013, Matthias Gelbmann

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