In the AI data infrastructure race, Oracle wants you to run AI inside your database. Not call an API. Not ship your data to an external LLM company. Not stand up a separate vector database. Run the whole thing on-prem, behind your firewall, managed by your data team. That’s what the Private AI Services Container […]
Running Oracle’s Private AI Stack On-Premises Read More »
Everyone is talking about AI. AI this, vector that, vector indexes eating your storage, running out of memory. I deployed 26ai on my lab cluster and went through the internals so you don’t have to guess what’s actually going on under the hood. Brace yourself for this DDL and DML ride. Here’s the short version
Oracle 26ai Vector Search Internals Read More »
Oracle 26ai came out. I deployed it, went to run my RMAN workflows, and immediately noticed things had changed. After an hour of reading through the 26ai Backup and Recovery documentation and testing against a live instance I found enough worth writing down. This post is part change log, part lab journal for what’s different
What Changed in RMAN for Oracle 26ai Read More »
Oracle 26ai can join external tables backed by S3 Parquet files with regular internal tables in a single SQL statement, without data movement, ETL pipelines, or Spark. The optimizer treats S3-backed external tables as another data source and picks the right join strategy automatically. This post shows how to build a customer dimension table from
Hybrid Analytics with Oracle 26ai and S3 Data Read More »
I spent months building a tool that answers a question nobody else was asking: how many databases can your infrastructure actually handle before something breaks? HammerDB-Scale orchestrates parallel database benchmarks on Kubernetes, correlates application metrics with storage behaviour, and finds consolidation limits. I also overengineered it for the wrong user experience. But I thought it
HammerDB-Scale 2.0 and Why I Rebuilt the Whole Thing Read More »
TL;DR: DBMS_CLOUD.CREATE_EXTERNAL_TABLE creates an external table that reads Parquet directly from S3. Define the table once, query it with standard SQL. No data loading, no ETL. With S3 connectivity working (Part 1 and Part 2), this post shows how to create DBMS_CLOUD external tables over Parquet files in S3 and query them from Oracle 26ai.
Querying Parquet Files on S3 with DBMS_CLOUD in Oracle 26ai Read More »
TL;DR: DBMS_CLOUD fails with non-AWS S3 because it parses hostnames to select the signing algorithm and extract the AWS region. Fix: point s3.us-east-1.amazonaws.com at your endpoint via DNS, add it as a SAN on the endpoint’s TLS cert, and import the cert into an Oracle wallet. Full DBMS_CLOUD functionality, no file downloads. In Part 1,
Solving DBMS_CLOUD Connectivity with S3-Compatible Storage Read More »
TL;DR: DBMS_CLOUD requires valid HTTPS certificates with matching hostnames. Self-signed certs or HTTP-only? DBMS_CLOUD won’t work. This post shows what breaks and why. Version Note: This uses Oracle 26ai (23.26.1.0.0). SSL handling behavior changed in 23ai. On 19c/21c, sqlnet.ora settings like SSL_SERVER_DN_MATCH=NO still work, so self-signed certs may be viable with additional configuration. The steps
Connecting Oracle 26ai to S3-Compatible Object Storage Read More »
