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Iceberg Vector Database
Serverless Vector Database & 4-Tier AI Agent Memory Engine
Sub-20ms serverless vector search, persistent agent memory, and hybrid RAG engine hosted natively in India.
Hey Product Hunt! 👋
While building RAG pipelines and autonomous AI agents in India, I kept hitting three walls with US-hosted vector databases:
1. 200ms+ round-trip latency to us-east-1 on every vector query.
2. Free tier pods pausing after a few days of inactivity.
3. Having to wire up external embedding APIs, BM25 + dense vector hybrid search, and TTL jobs for agent memory manually.
That's why I built Iceberg DB (https://icebergdb.in) — a serverless vector database and 4-tier AI agent memory engine hosted in Mumbai (ap-south-1) with sub-20ms latency.
What you get out of the box:
⚡ Sub-20ms Query Latency in India (DPDP Act 2023 compliant)
🔍 Built-in Hybrid Search (Dense + BM25 Reciprocal Rank Fusion)
🧠 Native 4-Tier AI Agent Memory (short_term, episodic, long_term, semantic)
📄 Built-in Neural Embeddings & direct PDF ingestion
📦 Official SDKs for Python (pip install iceberg-sdk), JS/TS (npm install iceberg-js), Rust, Go & .NET
🎁 Forever Free Tier (100,000 vectors, never pauses, no credit card required)
I'd love for you to test it live at https://icebergdb.in and share your feedback!
About Iceberg Vector Database on Product Hunt
“Serverless Vector Database & 4-Tier AI Agent Memory Engine”
Iceberg Vector Database was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #251 on the daily leaderboard. Sub-20ms serverless vector search, persistent agent memory, and hybrid RAG engine hosted natively in India.
On the analytics side, Iceberg Vector Database competes within Developer Tools, Artificial Intelligence and Database — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how Iceberg Vector Database performed against the three products that launched closest to it on the same day.
Who hunted Iceberg Vector Database?
Iceberg Vector Database was hunted by Iceberg DB. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Iceberg Vector Database including community comment highlights and product details, visit the product overview.
Iceberg DB