What this PR does / why we need it:

Oracle DB Offline Store for Feast (ibis-based)

This PR adds a native Oracle Database offline store for Feast, built on the ibis-framework's Oracle backend (ibis.oracle). It follows the same proven pattern used by the existing MSSQL ibis offline store — delegating to the shared ibis.py functions for point-in-time joins, deduplication, and feature retrieval.
The implementation is ~300 lines total (vs 1096 lines in the SQLAlchemy-based approach), with no Jinja2 templates, no dialect-specific SQL workarounds, and no manual query generation. ibis generates Oracle SQL automatically and provides native Arrow transfer via to_pyarrow().

Oracle Column Name Handling

Oracle stores unquoted identifiers in UPPERCASE. For example, CREATE TABLE t (user_id INT) stores the column as USER_ID. This store uses a passthrough approach — column names are returned exactly as Oracle stores them, with no automatic case transformation.
This means:
Unquoted columns (the standard Oracle convention): The user references them in UPPERCASE, matching what they see in Oracle tools like SQL Developer, DBeaver, or DESCRIBE table.
Quoted columns (e.g., "CamelCase"): The user references them with the exact casing used when creating the table.
This design ensures predictable behavior — what you see in Oracle is what you use in Feast. No hidden transformations, no conventions to learn.

How to Use

feature_store.yaml

project: my_project
provider: local
registry: data/registry.db

offline_store:
  type: oracle
  user: feast
  password: feast
  host: localhost
  port: 1521
  service_name: FREEPDB1

online_store:
  type: sqlite
  path: data/online_store.db

What's Tested

Tested against a live Oracle 23ai database (Oracle Free 23.26.1.0.0):

Core Feast Operations:

• Oracle connectivity via ibis.oracle.connect() with schema introspection
• feast apply — registering entities, feature views, and feature services
• get_historical_features — point-in-time correct feature retrieval with entity DataFrame
• materialize — pulling latest features from Oracle offline store into SQLite online store
• get_online_features — retrieving materialized features from the online store
• pull_all_from_table_or_query — direct offline store batch retrieval with date range filtering
• to_pyarrow() — native Arrow transfer via ibis (no intermediate pandas conversion)

Non-Entity Retrieval (entity_df=None):

• With both start_date and end_date provided
• With only end_date (start calculated from feature view TTL)
• With only start_date (end defaults to current time)
• With neither (end defaults to current time, start calculated from TTL)

Oracle Column Name Handling:

• Unquoted identifiers (UPPERCASE) — e.g., USER_ID, FEATURE_TIME, TXN_LAST_24H
• Quoted mixed-case identifiers — e.g., "User_ID" and "user_iD" in the same test run
• Full Feast flow (apply → historical → materialize → online) verified for both casing styles

Which issue(s) this PR fixes:

#6018

Misc