Netflix vs Prime vs Hotstar: Catalog & Pricing Data 2026

Author : Actowiz Solution | Published On : 03 Aug 2026

Introduction

TL;DR: Actowiz analyzed catalog metadata — 45,000+ title listings — and plan pricing across Netflix, Prime Video, and JioHotstar in India and the US. Findings: Prime Video listed the largest raw catalog while Netflix led in originals share; JioHotstar's regional-language depth (X% of its Indian catalog) is its structural moat; and per-title-value (catalog ÷ plan price) varies X× between markets for the same platform.

Why OTT Catalog Data Matters

Streaming competition is fought on three measurable axes: catalog breadth, content mix, and price architecture. Studios deciding licensing strategy, platforms benchmarking content gaps, and analysts modelling churn all need the same thing — structured, current catalog metadata. Platforms don't publish it; their public catalog pages reveal it.

Methodology

Platforms Covered: Netflix, Prime Video, and JioHotstar.
Markets Covered: India and the USA.
Title Listings Captured: 45,000+ movies and series (metadata only).
Metadata Fields Captured: Title, content type, genres, release year, language, audio and subtitle availability, maturity rating, original content flag, and add/remove dates.
Pricing Coverage: All subscription plan tiers, ad-supported plans, mobile-only plans, and bundle pricing.
Monitoring Window: 90-day tracking period with weekly catalog delta updates.

We capture listing metadata only — no media content — and track adds/removals to measure catalog churn.

Finding 1: Catalog Size vs Catalog Depth

Raw listed titles (India): Prime Video X > Netflix Y > JioHotstar Z.
Originals share: Netflix X%, Prime Y%, JioHotstar Z%.
Catalog churn: X% of titles rotated (added/removed) within 90 days — licensing-driven turnover is measurable weekly, and it's the signal behind "what's leaving" consumer anxiety.

Finding 2: Regional Language Is the Indian Battlefield

JioHotstar's catalog skews X% non-Hindi/non-English (Tamil, Telugu, Malayalam, Bengali...), versus Y% on Netflix and Z% on Prime. Combined with sports streaming, this explains its plan architecture: reach over ARPU. For content acquirers, the gap analysis by language × genre is a direct licensing-opportunity map.

Finding 3: Price Architecture & Per-Title Value

Entry Plan: Netflix – ₹XXX | Prime Video – ₹XXX | JioHotstar – ₹XXX.
Top Plan: Netflix – ₹XXX | Prime Video – ₹XXX | JioHotstar – 24.
Ad Tier Available: Netflix – Y/N | Prime Video – Y/N | JioHotstar – 12.
Titles per ₹100/Month (Entry Plan): Netflix – X | Prime Video – X | JioHotstar – 12.

US-vs-India comparison: the same platform's per-title value differs X× across markets — quantifiable evidence of regional price discrimination strategy.

Who Uses OTT Catalog Data

Studios & content owners: find genre/language gaps per platform to target licensing pitches.
Streaming platforms: benchmark catalog freshness, originals ratio, and pricing position.
Analysts & investors: catalog churn + pricing moves as leading indicators ahead of subscriber disclosures.
EPG/discovery apps: clean, current title metadata feeds.

FAQs

What exactly is in an OTT catalog dataset?

Listing metadata: titles, type, genres, languages, release years, maturity ratings, original flags, availability windows, and plan pricing — no media files or copyrighted content, only publicly visible catalog information.

How do you track titles leaving a platform?

Weekly catalog snapshots are diffed: titles present last week and absent this week are flagged as removals, building an add/remove history that measures licensing churn.

Can you cover other platforms and countries?

Yes — Disney+, Apple TV+, SonyLIV, Zee5, Max, Hulu, Crunchyroll and others, in any market where catalogs are publicly browsable; multi-country availability matrices are a common deliverable.

How current is plan pricing data?

Plan pages are monitored continuously; price changes, new ad tiers, and bundle changes are captured within 24 hours of going live.