In the modern business environment, where data-driven decision-making is the rule rather than the exception, it is now essential to operate in a highly optimized digital ecosystem. Among the main requirements of industries today are high-speed computing power, fully managed database services, and unlimited storage spaces. To bring these benefits to the table, users of the workhorse Oracle, which has been in use for decades, are increasingly looking to migrate their databases to a cloud environment.
This is where the question of migrating databases from Oracle to Snowflake arises. In this post, we will first examine Oracle and Snowflake as standalone entities, then compare the two, and finally explore the process of migrating databases from Oracle to Snowflake.
Oracle Database Management System
Oracle has been the go-to database management system for organizations worldwide for decades, largely due to its ability to run on various operating systems, including Windows Server, Unix, and GNU/Linux. Due to its networking stack feature, various applications can be seamlessly integrated into the Oracle database. Most critically, Oracle is ACID-compliant, the benchmark for data security, reliability, and data integrity.
Snowflake
Snowflake is a cloud-based data warehousing system available as a Software-as-a-Service (SaaS) product. It has been exclusively designed and created for the cloud platform and is neither built on any existing database nor “big data” software. Rather, Snowflake uses an SQL database engine with unique and distinctive features.
Since Snowflake operates exclusively in the public cloud infrastructure, there is no need to install, configure, or use additional hardware or software. All aspects related to management and maintenance issues are handled directly by Snowflake.
Benefits of Migrating Databases From Oracle To Snowflake
Before going into the “how” of the migration procedure, let us analyze the benefits that migrating databases from Oracle to Snowflake brings to the table and why Oracle users are increasingly opting for this procedure.
First, being based in the cloud, Snowflake offers unlimited storage facilities. Users can download the precise quantum of storage required by paying only for the resources used. If additional storage is required, it can be downloaded from the cloud in minutes for a fee. On the other hand, Oracle offers fixed storage space and rates, regardless of whether it is used or not. Hence, using Snowflake over Oracle is also a cost-saving proposition.
Snowflake offers high computing power. There is no degradation or drop in database performance, even when multiple users execute multiple intricate queries simultaneously. This significantly reduces wait times, thereby boosting workplace productivity.
Snowflake is optimized to accept data in its native form. There is no need to process and format data before inputting it into Snowflake, as it supports all forms of data, including unstructured, semi-structured, and structured data. This feature is not available in the Oracle database management system.
Snowflake is a fully managed service. Users can quickly set up their new data processing and analytics projects without needing to invest in additional hardware or software. These are some of the advantages of cloud-based databases that are also available on Snowflake.
It is for these cutting-edge and technically advanced features that it makes sense for businesses to move databases from Oracle to Snowflake.
How To Migrate Databases From Oracle to Snowflake
Four steps must be completed to migrate databases from Oracle to Snowflake
Step 1 – Extract Data From The Oracle Database.
Use the pre-installed SQL Plus query tool in the Oracle database to extract data from Oracle using the “Spool” command. The data will be extracted to a file specified in the command, which will continue running until it is switched off. Spool creates a new CSV file if one is not already present; however, if a file is already there, Spool will overwrite it by default.
Step 2 – Processing and Formatting the Extracted Data
The data so extracted in Step 1 cannot be directly loaded into Snowflake. It has to be first processed and formatted to match a structure that Snowflake supports.
These are the options available to users while loading data from Oracle to Snowflake.
- Snowflake supports major character sets, including ISO-8859-1 to 9, Big5, EUC-KR, UTF-8, and UTF-16, among others.
- Snowflake supports all SQL constraints, including UNIQUE, PRIMARY KEY, FOREIGN KEY, and NOT NULL.
- Snowflake supports various data types, including several primitive and advanced data types, as well as nested data structures.
- If none of these options are available, users can customize a format with the “File Format Option” to insert time or dates into a file in the table.
Step 3 – Loading Formatted Data to A Cloud Staging Area
Even after the data is formatted and processed, it cannot be loaded directly to Snowflake. Instead, it must be moved to a temporary location, which might be either an internal or external cloud staging area.
An internal staging area can be created in the form of a table to which a name, date, and file format are automatically allotted. For external staging areas, Snowflake currently supports Amazon S3 and Microsoft Azure. However, for an S3 external stage, IAM credentials with the required permissions must be obtained.
Step 4 – Loading Database From Staging Area To Snowflake
The final stage of the Oracle to Snowflake data migration process involves transferring data from the temporary staging area to Snowflake. For small databases, the internal data wizard can be used. For large databases, use the COPY INTO command.
Summing Up
We have seen how Snowflake supports SQL constraints. Another feature of Snowflake that enables the seamless handling of delta data loads is its support for row-level data manipulation. The primary motivation for this step is that it enables the incremental loading of mined data into a temporary table. From here, records can be modified and transferred to the final table.
