Snowflake is a data warehouse built for the cloud. Read more about Snowflake. The Etlworks Integrator includes several pre-built Flows optimized for Snowflake.
What can you do with Snowflake in Etlworks Integrator
ETL with Snowflake Using Snowflake-optimized Flows, you can extract data from any of the supported sources, transform, and load it directly into Snowflake |
Load multiple tables by a wildcard name You can load multiple databases objects (tables and views) by a wildcard name (without creating individual source-to-destination transformations) |
Setup incremental change replication using change data capture (CDC) Once the CDC is configured for the source database, you can create a CDC pipeline where the source is one of these databases and the destination is a Snowflake. |
Setup incremental Change Replication using a high watermark As in any other Flow type, it is possible to configure a Change Replication using high watermark. |
Bulk load files in Snowflake If you already have CSV, JSON, Parquet or Avro files in the local (server) or cloud storage and don't need to transform the data, the most efficient way to load these files into the Snowflake is to use the flow type Bulk load files into Snowflake
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Videos
How to load data into Snowflake A typical Snowflake-optimized flow does the following:
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Related resources
Extract, transform and load data in Snowflake Using Snowflake-optimized Flows, you can extract data from any of the supported sources, transform, and load it directly into Snowflake. |
Directly load files in Snowflake This Flow loads CSV or JSON files directly into Snowflake. The files can be anywhere, so long as the Etlworks Integrator can read them. |
ELT with Snowflake The Etlworks Integrator supports executing complex ELT scripts directly in Snowflake, which greatly improves the performance and reliability of the data ingestion.
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Work with Snowflake as a relational database You can use any |
Data type Mapping for Snowflake It is important to understand how we map various JDBC data types for the Snowflake data types. |
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Related case studies
eLearning company Streaming data from 1600+ MySQL databases to Snowflake using CDC
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"A typical CDC Flow can extract data from multiple tables in multiple databases, but having a single Flow pulling data from 55000+ tables would be a major bottleneck as it would be limited to a single blocking queue with a limited capacity. It would also create a single point of failure." |
Major retail chain Load data from 600+ SQL Servers behind a firewall
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"A major retail chain with stores across the US operates 600+ independent Microsoft SQL Server databases that work behind the firewall. They needed to consolidate data in the Snowflake data warehouse and the expected traffic from each location is tens of millions of records per day." |
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