DBMS > Hive vs. Microsoft SQL Server vs. MySQL vs. RRDtool vs. Vertica

System Properties Comparison Hive vs. Microsoft SQL Server vs. MySQL vs. RRDtool vs. Vertica

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

Widely used open source RDBMS

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Column oriented

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

hive.apache.org

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

www.mysql.com

oss.oetiker.ch/rrdtool

www.vertica.com

Technical documentation

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

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

dev.mysql.com/doc

oss.oetiker.ch/rrdtool/doc

vertica.com/documentation

Developer

Apache Software Foundation

initially developed by Facebook

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Tobias Oetiker

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

1989

1995

1999

2005

Current release

3.1.3, April 2022

SQL Server 2022, November 2022

8.4.0, April 2024

1.8.0, 2022

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V2 and FLOSS

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

C and C++

Implementations in Java (e.g. RRD4J) and C# available

C++

Server operating systems

All OS with a Java VM

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

HP-UX
Linux

Linux

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
ODBC
Thrift

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

ADO.NET
JDBC
ODBC
Proprietary native API

in-process shared library
Pipes

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C++
Java
PHP
Python

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

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

yes

proprietary syntax

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

by using the rrdcached daemon

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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