Treasure Data Customer Data Platform API
Treasure Data enterprise customer data platform REST API for large enterprises to ingest, unify, and activate customer data at petabyte scale with ML-powered segmentation, unified customer profiles, and multi-channel activation. Enables AI agents to manage data ingestion and bulk import for customer data collection automation, handle unified customer profile query for 360-degree customer view automation, access segment creation and audience management for customer targeting automation, retrieve job execution and workflow orchestration for data pipeline automation, manage database and table management for data organization automation, handle bulk export and data activation for downstream system automation, access ML model training and prediction for predictive analytics automation, retrieve query execution and result management for data analysis automation, manage event collection and stream ingestion for real-time data automation, and integrate Treasure Data with Salesforce, Adobe, Google Ads, Facebook, and martech platforms for end-to-end customer data activation.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Enterprise CDP. GDPR, SOC2, ISO27001. API key. US/EU/JP. Customer profile data.
⚡ Reliability
Best When
A large enterprise wanting AI agents to automate customer data ingestion, unified profile management, ML-powered segmentation, and multi-channel activation through Treasure Data's petabyte-scale enterprise CDP platform (Arm subsidiary).
Avoid When
JOB-BASED ASYNC PROCESSING FOR ALL BULK OPERATIONS: Treasure Data bulk operations (bulk import, query, export) are job-based and asynchronous; automated data pipelines must poll job status before accessing results; automated assumption of synchronous result returns empty result set for in-progress jobs. TD QUERY LANGUAGE AND PRESTO SQL: Treasure Data uses Presto SQL and TD Query for data analysis; automated query generation must produce TD-compatible SQL syntax; automated query using standard SQL with unsupported functions (PARTITION BY on some plans) creates query execution failure. CUSTOMER DATA VOLUME AND BILLING: Treasure Data pricing scales with data volume and monthly tracked users; automated high-volume data ingestion must model data volume costs; automated bulk ingestion without volume monitoring creates unexpected billing for large customer datasets.
Use Cases
- • Building unified customer profiles from CDP data automation agents
- • Creating audience segments from ML-powered targeting agents
- • Orchestrating data pipelines from ETL workflow automation agents
- • Activating customer data from martech integration agents
Not For
- • Small business customer data (use HubSpot or Klaviyo for SMB CDP)
- • Real-time event streaming (use Segment or mParticle for real-time CDP)
- • Self-service analytics (use Mixpanel or Amplitude for product analytics)
Interface
Authentication
Treasure Data uses API key for authentication. REST API with JSON. San Mateo, California HQ. Founded 2011 by Muga Nishizawa and Hiro Yoshikawa. Acquired by Arm Holdings in 2018 for $600M. Products: CDP, unified profiles, ML segmentation, data pipelines, audience activation. Integrations: Salesforce, Adobe, Google Ads, Facebook, Amazon. SOC2. ISO 27001. GDPR. Serves Fortune 500 enterprises. Competes with Segment, mParticle, and Adobe CDP for enterprise CDPs.
Pricing
San Mateo CA. Arm subsidiary. Custom enterprise pricing. $100K+/year. Annual contract.
Agent Metadata
Known Gotchas
- ⚠ ALL BULK OPERATIONS ARE JOB-BASED ASYNC: Treasure Data bulk import, query execution, and export all return job ID for async tracking; automated data pipeline must implement job status polling loop; automated synchronous assumption for bulk operations creates empty result handling for in-progress jobs
- ⚠ DATABASE vs TABLE vs COLUMN NAMING RESTRICTIONS: Treasure Data database and table names have character restrictions (lowercase alphanumeric, underscore); automated schema creation must sanitize names before API call; automated schema creation with names containing uppercase, spaces, or special characters creates validation error
- ⚠ TD QUERY vs PRESTO ENDPOINT DISTINCTION: Treasure Data has both TD Query API and Presto Query API with different SQL compatibility; automated query routing must select correct engine; automated Presto SQL using TD-specific functions fails on Presto endpoint; automated TD SQL using Presto-specific window functions may fail on TD Query endpoint
- ⚠ TIME COLUMN REQUIREMENT FOR ALL TABLES: Treasure Data requires a 'time' column (Unix epoch integer) in all tables for time-based partitioning; automated data ingestion must include Unix timestamp in 'time' column; automated data import without 'time' column creates schema validation error or incorrect time partitioning
- ⚠ MASTER SEGMENT vs BEHAVIOR TABLE QUERY PATTERN: Treasure Data separates master profile data (customer attributes) from behavior tables (events); automated customer analytics must join master segment with behavior tables for complete customer view; automated single-table query for full customer profile misses behavioral data in separate event tables
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Scores are editorial opinions as of 2026-03-07.