IP2Location™ LITE IP-COUNTRY-REGION-CITY-LATITUDE-LONGITUDE Database

introduzione Caratteristiche Campi database Configurazione del database Database di esempio AMI e immagini SDK e librerie Strumenti/Plugin gratuiti

introduzione

IP2Location LITE Database

 <a href="https://lite.ip2location.com" target="_blank">Geolocalizzazione IP</a>.

Inscrivez-vous gratuitement

Caratteristiche

Versione corrente	01 November, 2025
Prossimo aggiornamento	15 November, 2025
IPv4 Dimensione database	BIN: 69.99 MB CSV: 281.86 MB (2,999,594 Righe) CIDR: 329.46 MB (3,829,292 Righe)
IPv6 Dimensione database	BIN: 170.27 MB CSV: 739.72 MB (5,901,473 Righe) CIDR: 1.1 GB (11,942,838 Righe)
Vettore	Binario (BIN) File di testo ASCII (CSV)

Campi database

Nome	genere	Descrizione
ip_from	INT (10)^† / DECIMAL (39,0)^††	Il primo indirizzo IP mostra netblock.
ip_to	INT (10)^† / DECIMAL (39,0)^††	L'ultimo indirizzo IP mostra netblock.
country_code	CHAR(2)	Codice paese di due caratteri basato su ISO 3166.
country_name	VARCHAR(64)	Nome del paese basato su ISO 3166.
region_name	VARCHAR(128)	Nome della regione o dello stato.
city_name	VARCHAR(128)	Nome della città.
latitude	DOUBLE^†††
longitude	DOUBLE^†††

^† IPv4
^†† IPv6
^††† Latitude and Longitude are often near the center of population. These values are not precise and should not be used to identify a particular address or household.

Crea database

CREATE DATABASE ip2location;
USE ip2location;
CREATE TABLE `ip2location_db5`(
	`ip_from` INT(10) UNSIGNED,
	`ip_to` INT(10) UNSIGNED,
	`country_code` CHAR(2),
	`country_name` VARCHAR(64),
	`region_name` VARCHAR(128),
	`city_name` VARCHAR(128),
	`latitude` DOUBLE,
	`longitude` DOUBLE,
	PRIMARY KEY (`ip_to`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8 COLLATE=utf8_bin;

Importa database

LOAD DATA LOCAL
	INFILE 'IP2LOCATION-LITE-DB5.CSV'
INTO TABLE
	`ip2location_db5`
FIELDS TERMINATED BY ','
ENCLOSED BY '"'
LINES TERMINATED BY '\r\n'
IGNORE 0 LINES;

Crea database

CREATE DATABASE ip2location
GO

USE ip2location
GO

CREATE TABLE [ip2location].[dbo].[ip2location_db5](
	[ip_from] bigint NOT NULL,
	[ip_to] bigint NOT NULL,
	[country_code] nvarchar(2) NOT NULL,
	[country_name] nvarchar(64) NOT NULL,
	[region_name] nvarchar(128) NOT NULL,
	[city_name] nvarchar(128) NOT NULL,
	[latitude] float NOT NULL,
	[longitude] float NOT NULL
) ON [PRIMARY]
GO

CREATE CLUSTERED INDEX [ip_to] ON [ip2location].[dbo].[ip2location_db5]([ip_to]) ON [PRIMARY]
GO

Importa database

BULK INSERT [ip2location].[dbo].[ip2location_db5]
FROM '{PATH TO IP2LOCATION-LITE-DB5.CSV}'
WITH
(
	FORMATFILE = '{PATH TO DB5.FMT}'
)
GO

SQL Server 2016
SQL Server 2016 SQL Server 2014 SQL Server 2012 Azure SQL SQL Server 2008/2008R2 SQL Server 2005 SQL Server 2000 SQL Server 7.0 SQL Server 6.5

12.0
9
1 SQLCHAR 0 1 "\"" 0 first_double_quote  Latin1_General_CI_AI
2 SQLCHAR 0 20 "\",\"" 1 ip_from "",
3 SQLCHAR 0 20 "\",\"" 2 ip_to "",
4 SQLCHAR 0 2 "\",\"" 3 country_code Latin1_General_CI_AI,
5 SQLCHAR 0 64 "\",\"" 4 country_name Latin1_General_CI_AI,
6 SQLCHAR 0 128 "\",\"" 5 region_name Latin1_General_CI_AI,
7 SQLCHAR 0 128 "\",\"" 6 city_name Latin1_General_CI_AI,
8 SQLCHAR 0 20 "\",\"" 7 latitude "",
9 SQLCHAR 0 20 "\",\"" 8 longitude ""

Crea database

CREATE DATABASE ip2location WITH ENCODING 'UTF8';
\c ip2location
CREATE TABLE ip2location_db5(
	ip_from bigint NOT NULL,
	ip_to bigint NOT NULL,
	country_code character(2) NOT NULL,
	country_name character varying(64) NOT NULL,
	region_name character varying(128) NOT NULL,
	city_name character varying(128) NOT NULL,
	latitude real NOT NULL,
	longitude real NOT NULL,
	CONSTRAINT ip2location_db1_pkey PRIMARY KEY (ip_from, ip_to)
);

Importa database

COPY ip2location_db5 FROM 'IP2LOCATION-LITE-DB5.CSV' WITH CSV QUOTE AS '"';

Importa database

mongoimport -u USERNAME -p PASSWORD --authenticationDatabase admin --drop --db ip2location --collection ip2location_db5 --type csv --file "IP2LOCATION-LITE-DB5.CSV" --fields ip_from,ip_to,country_code,country_name,region_name,city_name,latitude,longitude

Crea database

CREATE DATABASE ip2location;
USE ip2location;
CREATE TABLE `ip2location_db5_ipv6`(
	`ip_from` DECIMAL(39,0) UNSIGNED,
	`ip_to` DECIMAL(39,0) UNSIGNED,
	`country_code` CHAR(2),
	`country_name` VARCHAR(64),
	`region_name` VARCHAR(128),
	`city_name` VARCHAR(128),
	`latitude` DOUBLE,
	`longitude` DOUBLE,
	PRIMARY KEY (`ip_to`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8 COLLATE=utf8_bin;

Importa database

LOAD DATA LOCAL
	INFILE 'IP2LOCATION-LITE-DB5.IPV6.CSV'
INTO TABLE
	`ip2location_db5_ipv6`
FIELDS TERMINATED BY ','
ENCLOSED BY '"'
LINES TERMINATED BY '\r\n'
IGNORE 0 LINES;

Crea database

CREATE DATABASE ip2location
GO

USE ip2location
GO

CREATE TABLE [ip2location].[dbo].[ip2location_db5_ipv6](
	[ip_from] char(39) NOT NULL,
	[ip_to] char(39) NOT NULL,
	[country_code] nvarchar(2) NOT NULL,
	[country_name] nvarchar(64) NOT NULL,
	[region_name] nvarchar(128) NOT NULL,
	[city_name] nvarchar(128) NOT NULL,
	[latitude] float NOT NULL,
	[longitude] float NOT NULL
) ON [PRIMARY]
GO

CREATE CLUSTERED INDEX [ip_to] ON [ip2location].[dbo].[ip2location_db5_ipv6]([ip_to]) ON [PRIMARY]
GO

Importa database

BULK INSERT [ip2location].[dbo].[ip2location_db5_ipv6]
FROM '{PATH TO IP2LOCATION-LITE-DB5.IPV6.CSV}'
WITH
(
	FORMATFILE = '{PATH TO DB5.FMT}'
)
GO

SQL Server 2016
SQL Server 2016 SQL Server 2014 SQL Server 2012 Azure SQL SQL Server 2008/2008R2 SQL Server 2005 SQL Server 2000 SQL Server 7.0 SQL Server 6.5

12.0
9
1 SQLCHAR 0 1 "\"" 0 first_double_quote  Latin1_General_CI_AI
2 SQLCHAR 0 39 "\",\"" 1 ip_from "",
3 SQLCHAR 0 39 "\",\"" 2 ip_to "",
4 SQLCHAR 0 2 "\",\"" 3 country_code Latin1_General_CI_AI,
5 SQLCHAR 0 64 "\",\"" 4 country_name Latin1_General_CI_AI,
6 SQLCHAR 0 128 "\",\"" 5 region_name Latin1_General_CI_AI,
7 SQLCHAR 0 128 "\",\"" 6 city_name Latin1_General_CI_AI,
8 SQLCHAR 0 20 "\",\"" 7 latitude "",
9 SQLCHAR 0 20 "\",\"" 8 longitude ""

Crea database

CREATE DATABASE ip2location WITH ENCODING 'UTF8';
\c ip2location
CREATE TABLE ip2location_db5_ipv6(
	ip_from decimal(39,0) NOT NULL,
	ip_to decimal(39,0) NOT NULL,
	country_code character(2) NOT NULL,
	country_name character varying(64) NOT NULL,
	region_name character varying(128) NOT NULL,
	city_name character varying(128) NOT NULL,
	latitude real NOT NULL,
	longitude real NOT NULL,
	CONSTRAINT ip2location_db1_pkey PRIMARY KEY (ip_from, ip_to)
);

Importa database

COPY ip2location_db5_ipv6 FROM 'IP2LOCATION-LITE-DB5.IPV6.CSV' WITH CSV QUOTE AS '"';

Importa database

mongoimport -u USERNAME -p PASSWORD --authenticationDatabase admin --drop --db ip2location --collection ip2location_db5_ipv6 --type csv --file "IP2LOCATION-LITE-DB5.IPV6.CSV" --fields ip_from,ip_to,country_code,country_name,region_name,city_name,latitude,longitude

Database di esempio


"ip_from","ip_to","country_code","country_name","region_name","city_name","latitude","longitude"
"0","16777215","-","-","-","-","0.000000","0.000000"
"16777216","16777471","AU","Australia","Queensland","Brisbane","-27.467540","153.028090"
"16777472","16778239","CN","China","Fujian","Fuzhou","26.061390","119.306110"
"16778240","16778495","AU","Australia","Victoria","Melbourne","-37.814007","144.963171"
"16778496","16778751","AU","Australia","Queensland","Warren","-23.500000","150.283330"
"16778752","16779007","AU","Australia","Victoria","Melbourne","-37.814007","144.963171"
"16779008","16779263","AU","Australia","Queensland","Warren","-23.500000","150.283330"
"16779264","16781311","CN","China","Guangdong","Guangzhou","23.127361","113.264570"
"16781312","16785407","JP","Japan","Tokyo","Tokyo","35.689497","139.692317"
"16785408","16793599","CN","China","Guangdong","Guangzhou","23.127361","113.264570"
"16793600","16794367","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16794368","16794623","JP","Japan","Hiroshima","Nuno","34.533330","132.400000"
"16794624","16794879","JP","Japan","Miyagi","Sendai","38.266990","140.867133"
"16794880","16795647","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16795648","16795903","JP","Japan","Hiroshima","Niho","34.369940","132.493950"
"16795904","16797695","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16797696","16797951","JP","Japan","Shimane","Izumo","35.367000","132.767000"
"16797952","16798207","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16798208","16798463","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16798464","16798719","JP","Japan","Tottori","Kurayoshi","35.433000","133.817000"
"16798720","16798975","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16798976","16799231","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16799232","16799487","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16799488","16799999","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16800000","16800255","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16800256","16800511","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16800512","16800767","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16800768","16801023","JP","Japan","Tottori","Yonago","35.432738","133.333399"
"16801024","16801279","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16801280","16801535","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16801536","16801791","JP","Japan","Tottori","Kurayoshi","35.433000","133.817000"
"16801792","16802047","JP","Japan","Tottori","Yonago","35.432738","133.333399"
"16802048","16802303","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16802304","16802815","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16802816","16803071","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16803072","16803327","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16803328","16803583","JP","Japan","Shimane","Izumo","35.367000","132.767000"
"16803584","16803839","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16803840","16804095","JP","Japan","Tottori","Yonago","35.432738","133.333399"
"16804096","16804351","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16804352","16804607","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16804608","16804863","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16804864","16805119","JP","Japan","Shimane","Izumo","35.367000","132.767000"
"16805120","16805375","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16805376","16805631","JP","Japan","Shimane","Izumo","35.367000","132.767000"
"16805632","16805887","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16805888","16806143","JP","Japan","Tottori","Yonago","35.432738","133.333399"
"16806144","16806399","JP","Japan","Tottori","Kurayoshi","35.433000","133.817000"
"16806400","16806655","JP","Japan","Yamaguchi","Shimonoseki","33.950000","130.933000"
"16806656","16806911","JP","Japan","Yamaguchi","Iwakuni","34.150000","132.183000"
"16806912","16807167","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16807168","16807423","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16807424","16807679","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16807680","16808447","JP","Japan","Shimane","Matsue","35.467000","133.050000"
"16808448","16808703","JP","Japan","Hiroshima","Hiroshima","34.385868","132.455433"
"16808704","16808959","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16808960","16809215","JP","Japan","Yamaguchi","Shimonoseki","33.950000","130.933000"
"16809216","16809471","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16809472","16809727","JP","Japan","Tottori","Tottori","35.500111","134.232839"
"16809728","16809983","JP","Japan","Yamaguchi","Yamaguchi","34.183000","131.467000"
"16809984","16810239","TH","Thailand","Chiang Rai","Pa Daet","19.504800","99.992430"
"16810240","16810495","TH","Thailand","Krung Thep Maha Nakhon","Bangkok","13.749976","100.516819"
"16810496","16810751","TH","Thailand","Phetchaburi","Phetchaburi","13.111890","99.944670"
"16810752","16811007","TH","Thailand","Songkhla","Songkhla","7.198820","100.595100"
"16811008","16811263","TH","Thailand","Suphan Buri","Don Chedi","14.634970","100.020970"
"16811264","16811519","TH","Thailand","Krung Thep Maha Nakhon","Bangkok","13.749976","100.516819"
"16811520","16811775","TH","Thailand","Ratchaburi","Ratchaburi","13.536710","99.817120"
"16811776","16812031","TH","Thailand","Chiang Rai","Wiang Chai","19.883610","99.933140"
"16812032","16812287","TH","Thailand","Prachuap Khiri Khan","Kui Buri","12.082830","99.854310"
"16812288","16812543","TH","Thailand","Trang","Ratsada","7.974670","99.633530"
"16812544","16812799","TH","Thailand","Nakhon Sawan","Takhli","15.263360","100.343780"
"16812800","16813567","TH","Thailand","Krung Thep Maha Nakhon","Bangkok","13.749976","100.516819"
"16813568","16813823","TH","Thailand","Phetchaburi","Phetchaburi","13.111890","99.944670"
"16813824","16814079","TH","Thailand","Krung Thep Maha Nakhon","Bangkok","13.749976","100.516819"
"16814080","16814335","TH","Thailand","Surat Thani","Koh Tao","10.098080","99.838090"
"16814336","16814591","TH","Thailand","Phatthalung","Phatthalung","7.617860","100.077920"
"16814592","16815103","TH","Thailand","Surat Thani","Ko Samui","9.535670","99.935670"
"16815104","16815359","TH","Thailand","Nakhon Si Thammarat","Thung Song","8.164530","99.680390"
"16815360","16815615","TH","Thailand","Phangnga","Takua Pa","8.870500","98.343830"
"16815616","16815871","TH","Thailand","Surat Thani","Ko Samui","9.535670","99.935670"
"16815872","16816127","TH","Thailand","Surat Thani","Koh Tao","10.098080","99.838090"
"16816128","16816383","TH","Thailand","Phangnga","Ko Yao","8.110140","98.592310"
"16816384","16816639","TH","Thailand","Phatthalung","Phatthalung","7.617860","100.077920"
"16816640","16816895","TH","Thailand","Surat Thani","Koh Tao","10.098080","99.838090"
"16816896","16817151","TH","Thailand","Surat Thani","Ko Pha Ngan","9.719450","99.995110"
"16817152","16817407","TH","Thailand","Surat Thani","Koh Tao","10.098080","99.838090"
"16817408","16817663","TH","Thailand","Krabi","Ban Ao Nang","8.045800","98.810350"
"16817664","16817919","TH","Thailand","Trang","Palian","7.172280","99.686330"
"16817920","16818175","TH","Thailand","Krabi","Ban Ao Nang","8.045800","98.810350"
"16818176","16818431","TH","Thailand","Surat Thani","Chaiya","9.386240","99.198610"
"16818432","16818943","TH","Thailand","Surat Thani","Ko Samui","9.535670","99.935670"
"16818944","16819199","TH","Thailand","Phangnga","Ban Phru Nai","7.933330","98.583330"
"16819200","16819455","TH","Thailand","Phatthalung","Khuan Khanun","7.734700","100.009310"
"16819456","16819711","TH","Thailand","Chiang Mai","San Pa Tong","18.628280","98.895720"
"16819712","16820223","TH","Thailand","Surat Thani","Ko Pha Ngan","9.719450","99.995110"
"16820224","16820479","TH","Thailand","Phetchaburi","Cha-am","12.800135","99.966107"
"16820480","16820735","TH","Thailand","Krung Thep Maha Nakhon","Bangkok","13.749976","100.516819"
"16820736","16820991","TH","Thailand","Surat Thani","Ko Samui","9.535670","99.935670"
"16820992","16821247","TH","Thailand","Phra Nakhon Si Ayutthaya","Wang Noi","14.226890","100.715500"
"16821248","16821759","TH","Thailand","Phatthalung","Phatthalung","7.617860","100.077920"
"16821760","16822015","TH","Thailand","Phangnga","Kapong","8.696970","98.409140"