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  • Snowflake vs Amazon⚔️|Free Oracle digital training and free certifications🎓|Oracle boosts multi-cloud strategy☁️|Google’s MCP Toolbox🛠️|Review of Oracle AI Vector Search Exam

Snowflake vs Amazon⚔️|Free Oracle digital training and free certifications🎓|Oracle boosts multi-cloud strategy☁️|Google’s MCP Toolbox🛠️|Review of Oracle AI Vector Search Exam

We are a little OCI skewed today - Don't count out Oracle

Author

Gladstone Benjamin
October 13, 2025

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What’s in today’s newsletter:

Also, check out the weekly Deep Dive - Review of Oracle AI Vector Search Exam, and Everything Else in Cloud Databases.

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CLOUD COMPUTING

TL;DR: Snowflake excels in cloud data warehousing with agile innovation and multi-cloud flexibility, while Amazon’s AWS dominates broader cloud infrastructure, offering investors a choice between specialized growth or diversified stability.

  • Snowflake specializes in cloud data warehousing with strong revenue growth and multi-cloud flexibility appealing to hybrid cloud users.

  • Amazon, through AWS, dominates cloud infrastructure with a broad service portfolio including computing, storage, and AI solutions.

  • Snowflake offers rapid innovation and data-centric market capture but faces scaling challenges compared to AWS’s vast ecosystem.

Why this matters: The Snowflake vs. Amazon comparison underscores a key investor dilemma between betting on rapid growth in specialized cloud data solutions or stable returns from a diversified cloud giant.

OCI

TL;DR: Oracle is strengthening multi-cloud support to boost flexibility and interoperability, competing with AWS and Azure, aiming to grow cloud services by helping clients avoid lock-in and optimize hybrid workloads.

  • Oracle is intensifying its multi-cloud strategy to compete with AWS and Microsoft Azure in cloud computing.

  • Oracle’s multi-cloud focus helps customers avoid vendor lock-in and efficiently manage hybrid workloads.

  • This approach may accelerate Oracle’s cloud growth and influence industry standards around enterprise cloud adoption.

Why this matters: Oracle’s enhanced multi-cloud strategy challenges dominant players by offering greater interoperability and flexibility, reducing vendor lock-in risks.

TL;DR: Oracle's "Race to Certification 2025" provides free digital training and certifications in AI, Oracle Cloud Infrastructure (OCI), Multicloud, and Oracle Data Platform, available from July 1 to October 31, 2025, with opportunities to earn rewards.

  • Oracle's "Race to Certification 2025" offers free digital training and certification exams in high-demand areas, including AI, OCI, Multicloud, and Data Platform

  • The program is a limited-time event, running from July 1 to October 31, 2025, and includes a competitive leaderboard with rewards for top participants

  • Participants can unlock rewards such as additional exam attempts and digital badges by progressing through different levels of training and certification

Why this matters: Oracle's "Race to Certification 2025" program offers a valuable opportunity for IT professionals to upskill and get certified in key cloud and AI technologies at no cost. This initiative helps to close the skills gap in the industry, and enables professionals to advance their careers.

IBM

TL;DR: IBM advances lakehouse environments by integrating data lakes and warehouses with improved governance, cataloging, and security tools, reducing complexity and enabling faster, scalable, compliant, and data-driven decision-making.

  • IBM enhances lakehouse environments by unifying data lakes and warehouses for flexible analytics and governance.

  • New tools improve data cataloging, lineage tracking, security, and interoperability across diverse data sources.

  • IBM’s platform reduces complexity, aiding IT teams with integrated management of structured and unstructured data.

Why this matters: IBM’s advancements in lakehouse technology break down data silos and simplify governance, empowering businesses to derive quicker insights while maintaining compliance.

GCP

TL;DR: Google's MCP Toolbox unifies database management with automated connectors, real-time sync, and monitoring, enhancing scalability, security, and efficiency for businesses of all sizes in cloud data integration.

  • Google’s MCP Toolbox offers a unified platform for connecting, managing, and monitoring multiple database types easily.

  • It features automated connectors, real-time synchronization, and robust monitoring tools for enhanced database integration.

  • The toolbox is designed for scalability and security, suitable for both small applications and large enterprise environments.

Why this matters: Google's MCP Toolbox simplifies complex database management by unifying diverse systems into one scalable, secure platform with automation and real-time sync.

EVERYTHING ELSE IN CLOUD DATABASES

DEEP DIVE
Review of Oracle AI Vector Search Exam

Sometimes I wonder to myself, why don’t I slow down, and open an establishment on 7 Mile Beach, and have Caribbean music blessing my ears everyday.

Well, that has not happened because I live in reality, and I have to bring you the news, and tell you what is happening in the real world. In our case, the cloud database world.

I just passed the Oracle AI Vector Search Professional (1Z0-184-25) exam this morning. This exam is a testament to one of threads that I have espoused throughout the existence of this newsletter - Data and AI technologies are blurring. We have all heard the chorus in the news that AI is going to take your job in the future. I don’t think that is the case if you are keen on learning new things.

What I would say is that you should, as a data practitioner is to keep close tabs on all of the modern database platforms that are not of the classic relational database realm, and of course keep abreast of developments in relational databases.

Oracle has added Vector functionality to their classic relational database offering. This is in the form of the VECTOR data type. As for this mornings exam, here are the domains that it will test you on:

  • Understand Vector Fundamentals, 20%

  • Using Vector Indexes, 15%

  • Performing Similarity Search, 15%

  • Using Vector Embeddings, 15%

  • Building a RAG Application, 25%

  • Leveraging related AI capabilities, 10%

Some of the subject covered are as follows:

  • Create Vector Indexes to speed up AI vector search

  • Create a RAG application using Python

  • Generate Vector Embeddings outside the Oracle database

  • Perform Exact Similarity Search

  • Perform Multi-Vector similarity search for multi-document search

  • Perform approximate similarity search using Vector Indexes

  • Understand Retrieval-augmented generation (RAG) concepts

  • Use Exadata AI Storage to accelerate AI vector search

  • Use HNSW Vector Index for search queries

  • Use IVF Vector Index for search queries

  • Use Vector Data type for storing embeddings and enabling semantic queries

One thing I took advantage of was the free training and free exam vouchers until October 31, 2025. Otherwise, you would be paying a hefty $321 USD for the exam voucher.

The exam itself is focused on particularly the new VECTOR data type. you need to know the DDL and DML associated with it, the indexes you can create that use VECTOR fields, and how you can employ vector embeddings.

As for the logistics of the actual sitting of the exam, I did this one at home. The proctoring experience was a lot more streamlined than in the past, and there were no technical hiccups.

The sign in process was smooth as all I really had to do was click a button in an email sent to me last night, to start the exam process.

The exam consists of 50 questions, and I was able to complete it in under an hour, after checking my answers.

All in all, a good experience. A good way to end the week, and commence with the long weekend.

BTW, Happy Thanksgiving to all of my Canadian subscribers! It’s hard, but don’t overdose on the tryptophan.

 

Gladstone Benjamin