DBMS > chDB vs. Drizzle vs. Microsoft Azure Table Storage vs. PlanetScale

System Properties Comparison chDB vs. Drizzle vs. Microsoft Azure Table Storage vs. PlanetScale

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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

An embedded SQL OLAP Engine powered by ClickHouse

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

A Wide Column Store for rapid development using massive semi-structured datasets

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	0.07
Rank	#376	Overall
	#158	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Website

github.com/chdb-io/chdb

azure.microsoft.com/en-us/services/storage/tables

planetscale.com

Technical documentation

doc.chdb.io

planetscale.com/docs

Developer

Drizzle project, originally started by Brian Aker

Microsoft

PlanetScale

Initial release

2023

2008

2012

2020

Current release

7.2.4, September 2012

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

commercial

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

C++

Server operating systems

server-less

FreeBSD
Linux
OS X

hosted

Docker
Linux
macOS

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.

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

with proprietary extensions

yes

with proprietary extensions

APIs and other access methods

JDBC

RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

C
C++
Java
PHP

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

optimistic locking

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights based on private key authentication or shared access signatures

Users with fine-grained authorization concept

no user groups or roles

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More resources

DB-Engines blog posts

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

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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