DBMS > Dragonfly vs. Drizzle vs. Hive vs. Microsoft SQL Server

System Properties Comparison Dragonfly vs. Drizzle vs. Hive vs. Microsoft SQL Server

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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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Microsofts flagship relational DBMS

Primary database model

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

hive.apache.org

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

Technical documentation

www.dragonflydb.io/docs

cwiki.apache.org/confluence/display/Hive/Home

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

Developer

DragonflyDB team and community contributors

Drizzle project, originally started by Brian Aker

Apache Software Foundation

initially developed by Facebook

Microsoft

Initial release

2023

2008

2012

1989

Current release

1.0, March 2023

7.2.4, September 2012

3.1.3, April 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

GNU GPL

Open Source

Apache Version 2

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++

Java

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
Windows

Data scheme

scheme-free

yes

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

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

SQL-like DML and DDL statements

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC

JDBC
ODBC
Thrift

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

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C
C++
Java
PHP

C++
Java
PHP
Python

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

Server-side scripts

Stored procedures

Lua

yes

user defined functions and integration of map-reduce

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

Triggers

publish/subscribe channels provide some trigger functionality

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

selectable replication factor

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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

Password-based authentication

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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