VS EXTERNAL VECTOR DATABASES
Why Run Two Databases When One Does Both?
Eliminate the separate vector database from your stack. HatiData includes built-in vector-indexed memory with SQL + semantic search, tags, TTL, and namespaces.
1
Database to Manage
$0
Memory Surcharge
SQL
+ Semantic Search
CONSOLIDATION
Eliminate the Vector DB from Your Stack
One Database, Two Workloads
Run analytical SQL queries and semantic vector search from the same connection. No data sync pipelines, no consistency headaches.
Zero Memory Surcharge
Vector-indexed memory is included in your HatiData deployment. No per-vector pricing, no separate storage tier, no surprise bills.
Tags, TTL, and Namespaces
Organize agent memory with metadata tags, automatic expiration via TTL, and namespace isolation. All queryable via SQL.
SQL + Semantic in One Query
Combine structured filters (WHERE, JOIN, GROUP BY) with semantic similarity search in a single SQL statement. No glue code required.
FEATURE COMPARISON
Built-In vs. Bolted-On
| Feature | External Vector Databases | HatiData |
|---|---|---|
| Architecture | Separate managed service, additional vendor | Built into HatiData, single deployment |
| Query Interface | Proprietary SDK / REST API | Standard SQL + semantic search functions |
| Memory Cost | Per-vector pricing, separate storage fees | Included, zero memory surcharge |
| Vendor Count | Warehouse + vector DB = 2 vendors | 1 vendor, 1 connection, 1 bill |
| Data Consistency | Eventual consistency across systems | Strong consistency, single source of truth |
| Latency | Network hop between warehouse and vector DB | In-process vector search, sub-millisecond |
| Agent Integration | Custom glue code for each agent framework | Native agent memory SDK with tags/TTL/namespaces |
| Compliance | Two vendors to audit, two DPAs to manage | Single VPC deployment, single audit surface |
Based on publicly available pricing documentation as of February 2026.
AGENT MEMORY
Purpose-Built for AI Agents
HatiData's agent memory layer gives every AI agent vector-indexed, namespace-isolated memory with automatic TTL expiration. Store conversation history, tool outputs, and retrieval-augmented context alongside your analytical data. Query both with standard SQL — no custom SDKs, no separate infrastructure, no sync pipelines.
One Database. Analytics + Agent Memory.
Stop paying for a separate vector database. Start with a zero-risk free tier or explore the agent memory documentation.