Businesses today are overflowing with data. The amount of data produced every day is truly staggering. Teradata, however, has simplified the process of managing and analyzing large volumes of data. Teradata makes it easy to capture, process, and store big or complex datasets.
The ever-evolving nature of technology brings in data complexities, data inconsistencies, and data integrity issues. But the rise of Snowflake, a modern data warehouse, has paved the way for modern data analytics.
For instance, Snowflake has developed a modern Cloud Data Warehouse solution capable of scaling automatically and independently, which is not possible with Teradata. This article talks about the steps involved in moving data from Teradata to Snowflake.
Note: Hevo doesn’t support Teradata as a source currently.
What is Snowflake?
Snowflake is a Cloud Data Warehousing solution provided as a SaaS offering. It is built on Amazon Web Service, Microsoft Azure, or Google Cloud infrastructure that provides an unbounded platform for storing and retrieving data. Snowflake Data Warehouse uses a different proprietary SQL Database Engine with a unique architecture designed for the cloud.
The architecture of Snowflake separates its “Compute” and “Storage” units, thereby scaling differently. This allows the customers to use and pay for both services independently. Like other popular Data Warehouses, it also uses Columnar Storage for parallel query execution.
With Snowflake, there is no hardware or software to select, install, configure, or manage, therefore, making it ideal for organizations that do not want to have dedicated resources for setup, maintenance, and support for in-house servers.
Snowflake security and sharing functionalities make it easy for organizations to quickly share and secure data in real-time using any available ETL solution. Snowflake’s architecture allows flexibility with Big Data. Snowflake is known for its scalability and relative ease of use when compared to other Data Warehouses in the market.
What is Teradata?
Produced by Teradata Corp, Teradata is a popular on-premise Relational Database Management System (RDBMS). It is best suited for organizations handling and analyzing huge amounts of data. It is highly scalable and is ideal for large Data Warehousing operations. Teradata made the transition to the Cloud a little late, but they are innovating constantly to retain their large customer base.
The Teradata Database system is based on Massively Parallel Processing (MPP) architecture. The MPP architecture divides the workload evenly across the system by splitting tasks among its processes and running them in parallel.
Teradata can be scaled up to about 2048 Nodes by simply increasing the number of AMPs. It supports the use of standard Structured Query Language (SQL) to connect to data stored in tables. Teradata finds its application in various organizations, enterprises, and businesses.
This method would require you to export existing DDL scripts or generate new DDL scripts to migrate to Snowflake. This is a time-consuming exercise and would need you to invest in Engineering Bandwidth.
Hevo provides a hassle-free solution and helps you directly migrate from a source of your choice to Snowflake without any intervention in an effortless manner. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code.
Hevo’s pre-built integration with Snowflake and 150+ Sources (including 50+ free Data Sources) will take full charge of the data transfer process, allowing you to migrate to Snowflake seamlessly and focus solely on key business activities.
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Teradata to Snowflake Migration: 2 Easy Methods
This article delves into 2 of the best ways for Teradata to Snowflake migration. Below are the 2 methods.
Method 1: Teradata to Snowflake Migration with DDL Scripts
Data migration from Teradata to Snowflake isn’t easy and requires you to follow a systematic process. You can follow these steps manually to migrate from Teradata to Snowflake.
Step 1: Moving your Data Model
To start with Teradata to Snowflake migration, you’ll need to move your Database Objects from Teradata to Snowflake. Depending on the scope of your initial migration, Database Objects include the Databases, Tables, Views, and Sequences in your existing Teradata Data Warehouse that you wish to move over to the Snowflake Data Warehouse.
There are several options for moving your data model from Teradata to Snowflake.
In addition to that, the user must set up a Snowflake Account before proceeding with Teradata to Snowflake migration.
Step 2: Setup Snowflake Account
At a minimum, the user who owns the Teradata Database must create a Snowflake Account to meet the needs. You can move over to their homepage to set up your account. Use the Snowflake UI to further create Accounts, Users, Databases, Warehouses, etc., on Snowflake.
Step 3: Migrating Existing DDL Scripts
After creating Snowflake Accounts and Databases, you can start creating the Database Structure. To do so, you’ll need to export the most recent version of DDL scripts from Teradata to Snowflake. Before migrating the DDL scripts, you need to edit them to make them compatible with Snowflake DDL. You need to remove code for extraneous features such as primary indexes and other storage or distribution-related clauses, that are not needed in Snowflake. You also need to replace the data types used in Teradata Scripts with the Snowflake-optimized data types. Below is a table that provides a mapping between Teradata and Snowflake data types.
Data Type Conversion Table
|Teradata Data Type||Snowflake Data Type|
|CHAR VARYING(n)||CHAR VARYING(n)|
Step 4: Creating New DDL Scripts
If you don’t have current DDL scripts for your Data Warehouse, you can generate new DDL scripts after extracting the metadata needed from the Teradata Data Dictionary. However, as discussed, primary indexes and storage clauses are not needed in Snowflake, hence you don’t need to extract metadata for them.
You only need basic DDL, such as CREATE TABLE, CREATE VIEW, and CREATE SEQUENCE. To generate new DDL scripts, you will need to write a SQL extract script. As discussed above, you need to convert the data types in your Teradata design to the Snowflake-optimized data types. However, you can directly code the data type conversions into the script instead of doing any manual search and replace process.
Once you have the scripts ready, you can log into your Snowflake Account and execute them.
Step 5: Load Data from Teradata to Snowflake
Your Snowflake Table is now ready to handle the historical data already loaded in your Teradata system. If you’re running Teradata on-premises, it is advisable to route the data to a Cloud Storage like AWS S3 before loading it into Snowflake. To do so, you will need to leverage Teradata Parallel Transporter (TPT) to extract the data for each table to one or more delimited flat files in text format. You can then upload these files into an AWS S3 staging bucket by using the PUT command. After moving the data into S3 buckets, you can start loading it into your Snowflake Table by using the COPY command.
Step 6: Connect Data Sources to Snowflake
After replicating all historical data from Teradata into Snowflake, you can directly connect Snowflake to the Data Sources that are written into Teradata. Make use of Snowflake’s JDBC drivers to load data programmatically into Snowflake from various sources. Many of the mainstream tools have native connectors to Snowflake.
Step 7: Decommission Teradata
Finally, Teradata to Snowflake migration is accomplished! You can now turn off all Teradata load processes and revoke access to Teradata.
Method 2: Move Data to Snowflake with Hevo
Hevo helps you directly transfer data from various sources to Snowflake, Business Intelligence tools, Data Warehouses, or a destination of your choice in a completely hassle-free & automated manner. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
Hevo can handle data type conversions automatically, saving you a tedious and potentially error-prone process. The following steps can be implemented to migrate from a source of your choice (Hevo doesn’t support Teradata as a source currently) to Snowflake using Hevo:
- Configure Source: Connect Hevo Data with a source of your choice by providing a unique name for your Pipeline, along with details about your Data Source.
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- Integrate Data: Establish a connection to Snowflake by providing information about your Snowflake Account and its credentials such as Database Name, Username, and Password.
Here are more reasons to try Hevo:
- Fully Managed: It requires no management and maintenance as Hevo is a fully automated platform.
- Data Transformation: It provides a simple interface to perfect, modify, and enrich the data you want to transfer.
- Real-Time: Hevo offers real-time data migration. So, your data is always ready for analysis.
- Schema Management: Hevo can automatically detect the schema of the incoming data and map it to the destination schema.
- Scalable Infrastructure: Hevo has in-built integrations for 150+ sources that can help you scale your data infrastructure as required.
- Live Monitoring: Advanced monitoring gives you a one-stop view to watch all the activities that occur within Data Pipelines.
- Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
Benefits of Teradata to Snowflake Migration
Below are some of the important pointers that are driving customers to a Teradata to Snowflake migration:
- Teradata charges you for both, storage and also compute power. Snowflake, on the other hand, charges about $1 a day per terabyte of storage. Migrating to Snowflake saves you time and other resources.
- Snowflake’s intuitive features like Compressing Data, Statistic Collection, Workload Management, and Disaster Recovery have been enticing more and more Teradata customers. Teradata, on the other hand, is more dba-driven, lacks advanced features, and requires much more maintenance and time.
- Snowflake has made migrating to the Cloud very easy. You can simply connect third-party products and services to Snowflake through a plugin instead of building a third-party API integration.
- Snowflake’s shared architecture separates “compute” from “storage” which allows automatic and instant scaling in a way not possible with Teradata.
- Snowflakes’ technology meets the needs of today’s business users, such as the increasing requirement for unlimited concurrency and performance.
Snowflake is a major player in the Cloud Data Warehousing industry and understanding how to migrate into it has become important. This article introduced you to Teradata and Snowflake and provided you with a step-by-step guide on Teradata to Snowflake migration through DDL scripts. Migrating to Snowflake with DDL scripts requires a lot of time and resources.
Migrating to Snowflake is a tedious and time taking process but a Data Integration tool like Hevo can perform this process with no effort and no time.
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Hevo Data, with its strong integration with 150+ Sources, allows you to not only export data from sources & load data in the destinations such as Snowflake, but also transform & enrich your data, & make it analysis-ready so that you can focus only on your key business needs and perform insightful analysis using BI tools. In short, Hevo can help you store your data securely in Snowflake.
Give Hevo Data a try and sign up for a 14-day free trial today. Hevo offers plans & pricing for different use cases and business needs!
Share your experience of working with Teradata to Snowflake migration in the comments section below.