DBMS > Drizzle vs. Microsoft Azure Table Storage vs. NSDb vs. PostgreSQL

System Properties Comparison Drizzle vs. Microsoft Azure Table Storage vs. NSDb vs. PostgreSQL

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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

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, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

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

nsdb.io

www.postgresql.org

Technical documentation

nsdb.io/Architecture

www.postgresql.org/docs

Developer

Drizzle project, originally started by Brian Aker

Microsoft

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2008

2012

2017

1989

1989: Postgres, 1996: PostgreSQL

Current release

7.2.4, September 2012

16.3, May 2024

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Apache Version 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Java, Scala

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
macOS

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

standard with numerous extensions

APIs and other access methods

JDBC

RESTful HTTP API

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C++
Java
PHP

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

Java
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

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

partitioning by range, list and (since PostgreSQL 11) by hash

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.

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

More information provided by the system vendor

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