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Build data-intensive applications without  operational burden

Snowflake’s Data Cloud is designed to power applications with no limitations on performance, concurrency, or scale. Trusted by fast growing software companies, Snowflake handles all the infrastructure complexity, so you can focus on innovating your own application.

Start for Free

High performance and unlimited concurrency

Snowflake’s multi-cluster, shared data architecture spins up additional compute clusters to support a near-unlimited number of concurrent users on shared tables without contention for resources.

SQL for all data

Use ANSI SQL to query structured and semi-structured data. Ingest JSON, Avro, Parquet, and other data without transformations or having to fix the pipeline every time the schema changes.

No SRE/DevOps burden

Developing and scaling data applications is complex. Snowflake automatically handles provisioning, availability, tuning, data protection, and other operations across multiple clouds for you.

scale automatically and cost-effectively

Powered by Snowflake

  • Lime

    Bike sharing app that shares rider data with cities so they can better plan infrastructure such as bike lanes and parking areas.

    News
  • HotelTonight

    Hotel Tonight built an online travel app that helps its hotel partners predict demand and improve their search ranking.

     

    Video
  • Instacart

    Grocery delivery app that enables CPG companies to make targeted offers based on store availability and customer behavior.

    Video
  • Blackboard

    Digital learning app that helps its educational institution customers predict and proactively improve student performance.

    Video
  • PDX

    Pharmacy management app that delivers insights from massive amounts of patient data securely to over 10,000 pharmacies.

    Case study
  • Heap

    Product analytics app to help its customers understand user behavior by securely sharing live data without having to copy it.

    Case study
  • Localytics

    Product analytics app that provides its customers instant access to data about their own customers’ in-app behavior.

    Video
  • Lacework

    Cloud security app that detects suspicious behavior that poses threats to its customers’ cloud workloads.

     

    Video
  • SG_Twilio_Lockup_Social
  • celtra-customer-logo-color@2x
  • healthgrades-customer-logo-color@2x
  • braze-customer-logo-color@2x
  • yonder-customer-logo-color@2x
  • amino-customer-logo-color
  • rakuten-customer-logo-color@2x

Features

Separation of compute and storage

Snowflake separates compute and storage so you can scale each independently and cost effectively.

Auto-scaling

Snowflake automatically scales compute resources, up and down, for near-infinite concurrency without impacting performance or having to reshuffle data.

Pay for what you use

Align costs with your product margins with per-second compute pricing and avoid paying for idle resources.

Native support for semi-structured data

Ingest and immediately query JSON, Parquet, Avro, ORC, and XML without defining schemas in advance.

Cross-cloud with global replication

Deploy on any cloud and regions, with global replication for high availability, data durability, and disaster recovery.

Zero-copy cloning

Quickly create sandboxes and develop pilots with live data but without the cost of copying and moving data.

Time travel

Easily access historical data after it has been modified or deleted for periods up to 90 days.

Connectors and drivers

Integrate easily with native clients and connectors including ODBC, JDBC, Node, Python, .NET, Go, Spark, and Kafka. Drivers for PHP and Ruby coming soon.

ANSI SQL

Use SQL for all your data, structured or semi-structured, including support for joins across data types, databases and external tables.

User-defined functions

Extend Snowflake with in-engine JavaScript functions to perform custom calculations.

Continuous data pipelines

Automate the steps to transform and optimize continuous data loads with Snowpipe and third-party data tools.

Secure data sharing

Share live data easily and securely with your partners but without copying or moving that data to ensure a single source of truth across your ecosystem.

SQL API

Programmatically make SQL calls to Snowflake without the need for client drivers or external API management infrastructure.

External tables

Query data in cloud object stores for additional insights but without having to ingest that data.

Access controls and encryption

Protect your customer data with role-based access controls (RBAC) and data encryption at rest and in transit.

Build using your language

  • Python
  • Node.js
  • Java
  • Go
  • .NET
  • SQL
import snowflake.connector
# Set your account details using connection = snowflake.connector.connect(...
 
cur = connection.cursor()
try:
  	cur.execute("SELECT col1, col2 FROM test_table ORDER BY col1")
  	for (col1, col2) in cur:
        	print('{0}, {1}'.format(col1, col2))
finally:
  	cur.close()
var snowflake = require('snowflake-sdk');

createConnectionObject = function () { /* Set account details using var */
    connection.connect(function(err, conn) { /* Add error-checking. */  } );
    connection.execute({
        sqlText: 'select * from ' + MY_DB + '.public.test_table',
        complete: function(err, stmt, rows) {
            for (var i = 0; i < rows.length; i++)  {
                console.log(rows[i]['COL1'] + ', ' + rows[i]['COL2']);
                }
            }
        });
}

createConnectionObject();
/* Add code to import java.sql.Connection, java.sql.DriverManager,
   java.sql.ResultSet, java.sql.Statement, java.util.Properties */

public class JDBCExample {
public static void main(String[] args) throws Exception {
   Properties properties = new Properties();

   // Set account details using properties.put(...
   Connection connection = DriverManager.getConnection(MY_CONNECT_STR, properties);
   Statement statement = connection.createStatement();
   ResultSet rs = statement.executeQuery("select * from test_table order by col1");
   while (rs.next()) {
      System.out.println(rs.getString(1) + ", " + rs.getString(2));
   }
   connection.close();
}
}
package main
import ( "database/sql"
         "fmt"
         sf "github.com/snowflakedb/gosnowflake" )
func main() {
    // Set account details using cfg := &sf.Config{...
    dsn, err := sf.DSN(cfg)
    if err != nil {fmt.Printf("ERROR")}
    db, err := sql.Open("snowflake", dsn)
    if err != nil {fmt.Printf("ERROR")}
    rows, err := db.Query("SELECT col1, col2 FROM " + MY_DB + "." + " public.test_table ORDER BY col1")
    defer rows.Close()
    var c1, c2 int
    for rows.Next() {
        err := rows.Scan(&c1, &c2)
        if err != nil {fmt.Printf("ERROR")}
        fmt.Printf("%d, %dn", c1, c2)
        }
    db.Close()    
}
using (IDbConnection conn = new SnowflakeDbConnection())
{
// Set account details using conn.ConnectionString = ...
 
    conn.Open();
    IDbCommand cmd = conn.CreateCommand();
	   cmd.CommandText = "SELECT col1, col2 FROM test_table ORDER BY col1";
	   IDataReader reader = cmd.ExecuteReader();          
    while(reader.Read())
    {
    	Console.WriteLine(reader.GetString(0) + " , " + reader.GetString(1));
	}
    conn.Close();
}
SELECT e.name as "DOCTOR",
       year(treatment_date) as "YEAR",
       d.name as "DIAGNOSIS",
       sum(t.cost_per_treatment)
       over (partition by doctor, year(treatment_date))
       as yearly_revenue
  FROM patients as p inner join treatments_applied as ta inner join
       treatments as t inner join diagnosis_types as d inner join employees as e
    ON ta.patient_ID = p.ID and
       ta.diagnosis_ID = d.ID and
       ta.treatment_ID = t.ID and
       e.ID = ta.doctor_ID
 WHERE lower(d.name) = 'python bite'
       -- extract from the JSON in the VARIANT column named "side_effects"
       and side_effects:physical.skin = 'pale'
  ORDER BY doctor, year(treatment_date);

Build data apps using the language of your choice including Python, Node.js, Go, .NET, Java, and SQL. Drivers for PHP and Ruby coming soon.

See our docs for complete working examples

Snowflake Documentation

Use Cases

  • Customer 360
  • IOT
  • Application Health and Security Analysis
  • Machine Learning and Data Science
  • Embedded Analytics

Build sales and marketing applications to accomplish 360-degree view customer goals, such as finding new segments and sending personalized offers using historical and real-time data

  • Enrich and monetize customer data with secure data sharing
  • Query data in cloud object storage with external tables without ingesting it
  • Query structured and semi-structured without ETL with ANSI SQL
See Reference Architecture

Develop applications that analyze large volumes of time-series data from IoT devices and respond in near real time.

  • Eliminate database sprawl with a single repository for all your device data with native support for semi-structured data
  • Easily stream data in real time with a native Kafka connector
  • Accelerate queries with automatic optimization for time-series device data
See Reference Architecture

Analyze large volumes of log data to identify potential security threats and monitor application health.

  • Analyze massive amounts of data cost effectively with commodity storage and per-second pricing
  • Implement SQL rules to detect anomalies with Snowflake Schedules and Tasks
  • Easily stream log data in real time with a native Kafka connector
See Reference Architecture

Train machine learning models to build predictive applications such as recommendation engines.

  • Build models with broad support of ML platforms, including AWS Sagemaker, Google ML Engine, DataRobot, Dataiku, H20.ai, Domino Data Labs and Zepl
  • Integrate ML libraries such as Tensorflow/Keras, PyTorch, Spark ML, and R Studio with native connectors for Python, SQLAlchemy and Spark
  • Leverage training data in your data lake without ingestion thanks to external tables
See Reference Architecture

Build data-intensive applications that deliver visualizations within your app.

  • Deliver fast analytics with workload isolation and auto scaling of near-infinite compute resources
  • Easily embed visualizations with connectors for embeddable tools such as Tableau and Looker or with open source charting libraries.
  • Easily deliver insights on all your data with native support for structured and semi-structured data
See Reference Architecture

LEARN MORE

7 Snowflake Reference Architectures for Application Builders

This ebook provides detailed reference architectures for seven use cases and design patterns.

Download Ebook

Little Book of Big Success with Snowflake

How 3 app developers are using Snowflake to accelerate customer onboarding, monitor brands on social media, and detect ad fraud.

Download Ebook

Best Practices for Building Data Apps on Snowflake

How developers can leverage the Data Cloud with seven best practices around architecture, deployment, and operations.

Download Ebook

POWERED BY SNOWFLAKE

Powered by Snowflake Program helps software companies build, operate, and grow applications.

 APPLY NOW

PUBLIC PREVIEW ANNOUNCEMENT: Snowpark

Use language of your choice and familiar data frame constructs to build powerful and efficient pipelines and apps with the performance and ease-of-use of the Snowflake’s processing engine.

READ THE BLOG   TRY THE HANDS-ON GUIDE


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