Solution: Real-Time Data Lakehouse for SaaS providers

Why SaaS Leaders Choose a New Data Infra

Rising Costs of Real-Time

Streaming (e.g., Flink) is too expensive to scale across all data.

Complex Multi-Tenant Ops

Sharding, schema management, and ops drain your team’s focus.

Insecure Data Sharing

Copying data for partners & customers is slow and ungoverned.

AI Demands a New Stack

Traditional warehouses can’t support unstructured data + AI pipelines.

’‘ SaaS leaders need a simpler, more efficient, and future-proof way to manage data at scale. ’‘

Built for SaaS Real-Time, Secure, and Cost-Efficient

Singdata Lakehouse delivers a modern data foundation designed specifically for SaaS workloads.

Massive Real-Time Data Integration

Seamlessly unify fragmented SaaS data into a single real-time foundation—scalable, resilient, and ready for millions of tables.

Real-time integration for 10M+ tables across sharded databases

Support mirror sync or schema merge

Built-in fault recovery for resilience

Next-Gen Real-Time Processing

Cost-based incremental execution brings real-time analytics within reach—faster, simpler, and up to 10× cheaper than Flink.

Data visible in seconds with incremental real-time ingestion

Up to 10× cheaper vs Flink, powered by Generic Incremental Compute

Sub-second interactive queries with interactive real-time analytics

Stable high-concurrency serving for BI dashboards and SaaS applications

Zero-Copy, Governed Data Sharing

Share data securely across tenants and partners—instantly, without duplication, and under full governance control.

Share data instantly across accounts and services

Full access governance with one-click revoke

No extra storage cost for consumers

SaaS Use Cases That Deliver

Singdata Lakehouse solves the toughest SaaS data challenges—real-time, cost efficiency, scalability, and secure collaboration—through proven, high-impact use cases.

Real-Time at Lower Cost

Elastic BI at Any Scale

Secure, Zero-Copy Data Sharing

Challenge

Real-time pipelines are prohibitively expensive with Flink), forcing teams to limit real-time to only core data while leaving the rest offline. This causes data inconsistency and high maintenance overhead.

Solution

Dynamic Tables with GIC, enable cost-based incremental processing reduce real-time costs dramatically. Elastic Virtual Clusters ensure pay-as-you-go efficiency.

Impact

Achieve full-domain real-time at up to 10× lower cost vs Flink—without exceeding offline budgets.

’‘ This reference architecture illustrates how SaaS providers can simplify operations, improve performance, and reduce cost by consolidating into a single-engine Lakehouse platform. ’‘

Proven with Leading SaaS Innovators

From CRM to retail SaaS, leading companies run their mission-critical data on Singdata Lakehouse— achieving real-time scale, lower cost, and new business value.