A Guide to Replicating Oracle Data to Snowflake
Since the year 1991 when the Oracle database was launched commercially, it has been leading the data landscape in organizations. It is primarily because of the many unique features of the Oracle database. It helps in quick and safe retrieval and storage of data and can run on a wide range of hardware and software operating systems. Oracle was one of the first databases to have supported GNU/LINUX. Being ACID-compliant it ensures data integrity and data reliability.
Given all these pluses, why would organizations want to replicate data Oracle to Snowflake?
The Benefits of Snowflake
Snowflake is a comparatively recently introduced cloud-based data warehousing solution offered as a Software-as-a-Service (SaaS) product. It is not dependent on any “big data” software or existing database as it operates exclusively on the cloud. Instead, Snowflake uses a new SQL database engine that has a host of additional functionalities and capabilities when measured against other traditional databases.
Why Replicate Data Oracle to Snowflake
A huge advantage of Snowflake is that it runs fully on the cloud infrastructure. Users do not have to invest in and install, manage, or configure any additional hardware and software. All tuning and maintaining issues are taken care of directly by Snowflake.
A very critical aspect offered by Snowflake that makes organizations want to replicate data Oracle to Snowflake is data safety and security. The database automatically encrypts data with federated and multi-factor authentication, ensuring that there is no data leak or data breach. Snowflake follows strict security standards as mandated by HIPAA about access control from data objects to activities within the database.
Another feature that has been recently added to Snowflake is database replication, making moving data from Oracle database to Snowflake that much easier. The Standard version enables secured data sharing across the cloud and regions. Thus data portability becomes smooth and this helps to load databases from other databases like Oracle or Microsoft SQL Server. The older Enterprise for Sensitive Data (ESD) version had a Database Failover and Fallback feature that is to be paid for only when used.
The ESD model is especially useful in the modern business environment where organizations around the world are almost fully data-driven. The Database Failover and Fallback feature make sure of quick fallback and failover activity for seamless data recovery in the event of an outage. There is no break in activities as secondary databases operating in the region are automatically triggered and take up the load, acting as temporary primary databases. After the outage is resolved, the failback and failover work in the reverse direction, the primary databases are refreshed and activated and normal workloads are resumed. The whole process works without any human intervention.
This feature is enough to make users want to replicate data Oracle to Snowflake.
Steps to Replicating Data Oracle to Snowflake
There are several steps for replicating data Oracle to Snowflake.
- Step1 – The process starts with extracting data from the Oracle database. The SQL Plus query tool in the Oracle Database Server is used to query and then transfer the result of the query to a CSV file through the “Spool” command. An existing CSV file will be overwritten by “Spool” by default but if no file exists, a new one will be automatically created.
- Step 2 – The data so extracted has to be processed and formatted now. It has to be ensured that the data type at source in the Oracle database matches with the data structures supported by the Snowflake architecture. An advantage is that Snowflake supports all major character sets. These include ISO-8859-1 to 9, Big5, EUC-KR, UTF-8, UTF-16, and other primitive and advanced data types. However, it is advisable to be sure in this regard before trying to replicate data Oracle to Snowflake.
- Step 3 – The processed and formatted data cannot be directly loaded to Snowflake. It has to be kept in a temporary location known as staging. There are two components here – Internal and External Stages. In an Internal stage, a table has to be created and a specific name allotted to it. File format and date format options are auto-applied. For the External stage, Snowflake currently supports only Amazon S3 and Microsoft Azure.
- Step 4 – This is the final step where data is copied from the staging area to an intended table in Snowflake. The command to do so is “COPY INTO” for which credits are utilized and compute resources in Snowflake are required.
Follow these simple steps to replicate data Oracle to Snowflake.