DBMS > Drizzle vs. KairosDB vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. Oracle Rdb

System Properties Comparison Drizzle vs. KairosDB vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. Oracle Rdb

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.

Distributed Time Series DBMS based on Cassandra or H2

Globally distributed, horizontally scalable, multi-model database service

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Website

github.com/kairosdb/kairosdb

azure.microsoft.com/services/cosmos-db

www.microsoft.com/en-us/sql-server

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

kairosdb.github.io

learn.microsoft.com/azure/cosmos-db

learn.microsoft.com/en-US/sql/sql-server

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Drizzle project, originally started by Brian Aker

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2008

2013

2014

1989

1984

Current release

7.2.4, September 2012

1.2.2, November 2018

SQL Server 2022, November 2022

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

Linux
OS X
Windows

hosted

Linux
Windows

HP Open VMS

Data scheme

yes

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

APIs and other access methods

JDBC

Graphite protocol
HTTP REST
Telnet API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C
C++
Java
PHP

Java
JavaScript

Node.js
PHP
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

hooks for callbacks inside the server can be used.

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

yes, on a single node

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

simple password-based access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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