A Comprehensive Guide to Oracle to Snowflake Data Replication Tools

Oracle as a database has several advantages and has been used by organizations to execute critical workloads and increase operational efficiencies. It has also been the leader in the data landscape for decades. Then why is it necessary to replicate data Oracle to Snowflake? To understand this aspect fully, it is necessary to know what Snowflake is and the benefits it offers.

Snowflake

Snowflake is a comparatively newly-introduced cloud-based data warehousing solution and is available as a Software-as-a-Service (SaaS) product. It operates exclusively on the cloud and is not dependant on any “big data” software or an existing database. Rather, it makes use of a new SQL database engine that has specific capabilities and functionalities. All management, tuning, and maintenance issues are taken care of in Snowflake without having to install, configure, and operate hardware and software. It is thus a quantum improvement over traditional data warehousing solutions.

Benefits of Snowflake

There are several benefits of Snowflake that make organizations want to replicate data Oracle to Snowflake.

It is very difficult in Oracle to work with both structured and unstructured data. In Snowflake, users can work effortlessly with both of them.
Being a fully managed service, businesses can rely on Snowflake to have their data processing projects and analytics up and running speedily without any investment in hardware or software.
Users can scale up and down as per the requirement of resources and pay for quantum used only. This agility and elasticity are unmatched amongst data warehousing solutions.
Snowflake provides a high computational capability to users. Even when multiple users are running multiple intricate queries, there is no drop in performance and any drag or slowdown.

While the process to replicate data Oracle to Snowflake is seamless and trouble-free, it is necessary to make the right choice of tools. This helps Database Administrators to avoid going through tedious and complicated procedures.

Choosing the right tool for data replication

The most optimized tool for data replication from Oracle to Snowflake will have certain specific attributes. Choosing one that has them all will make the replication task easier.

Fully automated tool – With a completely automated tool, users do not have to set up pipelines and connectors to replicate data and coding is not required at any stage. The whole cycle of data mergers, data transformation, and data reconciliation is done through a user-friendly point and click interface.
Able to replicate large data volumes – In the modern business environment, enterprises have to deal with massive volumes of data. Most tools available today fail when such quantum of data has to be replicated. Choose a tool that can handle terabytes of data easily and effortlessly.
Maintain referential integrity of data – It is critical to precisely know the date, time, and values that changed at the columnar level after replication. This is known as referential integrity. The best tool will ensure that this is maintained at all times.
Reconciling data in Snowflake – The most preferred tool should be one that can continually reconcile data in the Snowflake cloud warehouse with the Oracle database that is replicated. It should check in detail, columns checksum and row count in the Oracle database with that in Snowflake.
Using Changed Data Capture – The traditional replication tools refresh full data to destination data in the event of any modification of data at source. This process is a time-consuming one. The top tool to replicate data Oracle to Snowflake will use Oracle Changed Data Capture (CDC) and will copy only the incremental changes into the Snowflake database.
Reduced Workloads for DBAs – Database Administrators usually have a difficult time during replication with traditional tools and Total Cost of Ownership (TCO) can only be worked out after the process is completed. With an automated tool, the DBAs are not directly involved at any stage, thereby reducing the TCO.