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1. LOADING DATA INTO
SNOWFLAKE (BULK & STREAM)
A COMPREHENSIVE GUIDE

2. WHAT IS DATA LOADING IN
SNOWFLAKE?
DATA LOADING IS THE PROCESS OF IMPORTING DATA
FROM EXTERNAL SOURCES INTO SNOWFLAKE TABLES SO
IT CAN BE QUERIED, ANALYZED, AND TRANSFORMED.
• TYPES OF LOADING:
• BULK LOADING: IMPORTING LARGE VOLUMES AT
ONCE (E.G., 1 MILLION ROWS FROM CSV FILES).
• STREAM LOADING: CONTINUOUSLY INGESTING
SMALL PIECES OF DATA (E.G., USER CLICKSTREAM
DATA).
EXAMPLE:
• LOADING 5 YEARS OF CUSTOMER DATA → BULK
LOAD
• LOADING CUSTOMER LOGIN EVENTS IN REAL TIME →
STREAM LOAD
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3. WHAT IS BULK LOADING?
• LOADING LARGE FILES IN ONE GO FROM FLAT FILES LIKE .CSV, .JSON, .PARQUET.
WHEN TO USE:
• DATA MIGRATIONS, NIGHTLY DATA REFRESHES, BATCH REPORTING.
WHY IT'S USED:
• FASTER THROUGHPUT WHEN DEALING WITH HIGH VOLUMES.
• LOWER FREQUENCY, COST-EFFECTIVE FOR NON-TIME-SENSITIVE DATA.
EXAMPLE:
• UPLOADING DAILY SALES REPORTS FROM S3 USING COPY INTO EVERY NIGHT.
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4. HOW BULK LOADING WORKS IN SNOWFLAKE
STEP-BY-STEP PROCESS:
1 . PREPARE YOUR FILES: ORGANIZE CSV/JSON FILES IN CLOUD STORAGE (S3, AZURE BLOB).
2 . CREATE STAGE IN SNOWFLAKE: TEMPORARY OR PERMANENT STORAGE REFERENCE.
CREATE OR REPLACE STAGE my_s3_stage
URL='s3://mybucket/data'
CREDENTIALS=(aws_key_id='xxx'
aws_secret_key='yyy');
Example:
3 . Use COPY INTO Command: Load data into a target table.
COPY INTO my_table FROM @my_s3_stage FILE_FORMAT=(TYPE=CSV);
4 . Validate Load: Use VALIDATION_MODE='RETURN_ERRORS'
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5. WHAT IS STREAM LOADING?
• REAL-TIME OR NEAR REAL-TIME DATA INGESTION USING SNOWPIPE, KAFKA, STREAMS & TASKS.
WHEN TO USE:
• WHEN DATA FRESHNESS IS CRUCIAL — IOT DEVICES, STOCK MARKETS, OR FRAUD DETECTION
SYSTEMS.
WHY IT'S IMPORTANT:
• ENABLES RESPONSIVE, ALWAYS-UPDATED DASHBOARDS AND ALERTS.
EXAMPLE:
• REAL-TIME SENSOR DATA FROM TEMPERATURE DEVICES SENT EVERY 10 SECONDS → LOADED USING
KAFKA → SNOWFLAKE VIA SNOWPIPE.
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6. TOOLS FOR STREAM LOADING IN SNOWFLAKE
• 1. SNOWPIPE:
• MONITORS CLOUD STORAGE AND LOADS DATA AUTOMATICALLY UPON ARRIVAL.
• AUTO-INGESTION VIA AWS S3 EVENTS OR API TRIGGERS.
EXAMPLE:
CREATE PIPE my_pipe
AS COPY INTO real_time_table
FROM @iot_stage FILE_FORMAT = (TYPE = JSON);
2. Kafka Connector for Snowflake:
• Integrates Apache Kafka for real-time ingestion.
• Streams topics from Kafka directly into Snowflake.
3. Streams & Tasks:
• Streams: Track changes (INSERT/UPDATE/DELETE) on tables.
• Tasks: Schedule SQL logic on those changes.
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7. BULK VS STREAM – DEEP COMPARISON
Feature Bulk Load Stream Load
Frequency Scheduled (e.g., hourly/daily) Continuous (real-time or near-
real-time)
Volume High-volume Small, incremental
Tools Used COPY INTO, SnowSQL Snowpipe, Kafka Connector,
Streams & Tasks
Data Freshness Lower (latency from schedule) High (almost immediate
updates)
Use Cases Reporting, archival data, batch
ETL
Dashboards, fraud detection, IoT
sensors
Setup Complexity Moderate Slightly higher (more moving
parts)
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8. BULK LOAD TIPS:
• COMPRESS FILES (GZIP/SNAPPY) TO REDUCE STORAGE AND IMPROVE SPEED
• USE FILE FORMATS LIKE PARQUET FOR COMPLEX NESTED DATA
• TEST WITH VALIDATION_MODE BEFORE FULL EXECUTION
• OPTIMIZE PARALLEL LOADING BY SPLITTING FILES
STREAM LOAD TIPS:
• USE EXTERNAL NOTIFICATION INTEGRATION (E.G., AWS SNS FOR S3 UPDATES)
• MONITOR LOADS WITH SNOWFLAKE’S LOAD HISTORY VIEWS
• USE STREAMS & TASKS FOR TRANSFORMATION PIPELINES POST-INGESTION
• ISOLATE INGESTION WAREHOUSES FOR CONCURRENCY
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9. KEY TAKEAWAYS: CHOOSE BULK LOADING
FOR VOLUME, STREAM
LOADING FOR SPEED
SNOWFLAKE PROVIDES
NATIVE SUPPORT FOR
BOTH VIA EASY SQL-BASED
CONFIGURATIONS
INTEGRATION OPTIONS
INCLUDE S3, KAFKA, AND
PYTHON APIS
AUTOMATION VIA
SNOWPIPE, STREAMS, AND
TASKS ENABLES POWERFUL
PIPELINES
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10. CONTACT DETAILS
• CONTACT@ACCENTFUTURE.COM
• ACCENTFUTURE
• +91-96400 01789
contact@accentfuture.com +91-96400 01789