DBMS > Blueflood vs. Drizzle vs. Microsoft Azure SQL Database vs. StarRocks

System Properties Comparison Blueflood vs. Drizzle vs. Microsoft Azure SQL Database vs. StarRocks

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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

Scalable TimeSeries DBMS based on Cassandra

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

Database as a Service offering with high compatibility to Microsoft SQL Server

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	0.95
Rank	#193	Overall
	#89	Relational DBMS

Website

blueflood.io

azure.microsoft.com/en-us/products/azure-sql/database

www.starrocks.io

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.microsoft.com/en-us/azure/azure-sql

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Rackspace

Drizzle project, originally started by Brian Aker

Microsoft

The Linux Foundation

since Feb 2023

Initial release

2013

2008

2010

2020

Current release

7.2.4, September 2012

V12

3.3, June 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

commercial

Open Source

Apache Version 2.0

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

C++

C++, Java

Server operating systems

Linux
OS X

FreeBSD
Linux
OS X

hosted

Linux

Data scheme

predefined scheme

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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

HTTP REST

JDBC

ADO.NET
JDBC
ODBC

JDBC
MySQL protocol

Supported programming languages

C
C++
Java
PHP

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

Java

Server-side scripts

Stored procedures

Transact SQL

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

yes, with always 3 replicas available

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.

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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More resources

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