Data as a Service (DaaS)
Publish consolidated business-domain datasets as real-time APIs — modeled once, reused everywhere.
TapData DaaS consolidates heterogeneous data into a domain-oriented (e.g., Customer, Order, Inventory) access layer. Capture changes with CDC, compose shared entities, and expose them as versioned REST APIs, datasets, or streams—so apps, partners, and analytics consume trusted, up-to-date data without caring where it’s stored or how it’s shaped.
Why DaaS Now？
Building ETL pipelines for every data need is not scalable and manageable —The teams need reusable, contract-driven data services.
Products and partners expect API-ready data with clear semantics and versioning.
Operations and analytics demand real-time data—OLTP and OLAP alike.
Governance and compliance require access control, auditability, and consistent definitions.
What DaaS Is
A centralized domain API layer over virtualized disparate data sources—not just pipelines—delivered with contracts, governance, and SLAs.
How It Works
Connect — 100+ types of sources/targets with log-based CDC (read logs, not queries).
Transform and Model — Abstract schemas into domain entities/metrics with unified semantics; catalog and discover datasets/services.
Accelerate — Use a platform cache and incremental materialized views to keep query responses lightning fast.
Serve — No/low-code publishing of versioned REST APIs, datasets (JSON/CSV/Parquet), and event/webhook streams; auto-generated docs.
Govern & Monitor — RBAC, masking/tokenization, audit logs, lineage, usage analytics, and SLAs.
Reference Architecture
Industry Example
Chow Sang Sang (Retail Jewelry)
TapData DaaS unified and governed product & inventory data across four regions and six brands, consolidating 10+ ERP/POS/WMS systems into a single data service. It then publishes versioned REST APIs (e.g., /products, /inventory/availability, /pricing) and incremental materialized views so e-commerce, stores, marketplaces, and franchise partners see consistent, up-to-date stock and catalog data in real time—backed by RBAC/audit and a platform cache to protect source systems.
Implementation pattern:
Outcomes
Faster delivery: ship data products in days, not months.
Consistency at scale: one contract, many consumers; fewer breaks across channels.
Lower source load: platform cache and incremental views reduce production impact.
Governed access: RBAC, masking, lineage, and full audit trail for compliance.
FAQ
Q1: How is DaaS different from an API gateway?
Gateways route traffic; DaaS provides the governed data layer access, domain semantics, contracts, versioning, and always-fresh delivery.
Q2: Can DaaS support both applications and analytics?
Yes. DaaS can serve both applications and analytics with a focus on the former.
Q3: How do we avoid load on production systems?
Log-based CDC, a platform cache, and incremental materialized views serve requests without heavy queries on sources.
