’‘ SaaS leaders need a simpler, more efficient, and future-proof way to manage data at scale. ’‘
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.
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
Powered by Generic Incremental Compute
Cost-based incremental execution brings real-time analytics within reach—faster, simpler, and up to 10x cheaper than Flink.
Data visible in seconds with incremental real-time ingestion
Up to 10x 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
Powered by Generic Incremental Compute
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 10x 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.
Real-Time Data at
Internet Scale
Unified 10M+ tables into a single real-time platform
Reduced compute costs by 50% with incremental processing
Achieved 10x efficiency vs legacy streaming pipelines
Powering Real-Time
Multi-Tenant CRM
Synced 8,000+ tables with millisecond freshness
Delivered interactive BI at sub-4s latency for Fortune 500 clients
Ensured 100% consistency across tenants under high concurrency
Fully Managed Data Platform for Membership Insights
Cut TCO by 40% with elastic, pay-as-you-go Lakehouse
Freed engineering from ops to focus on customer value
Enabled secure zero-copy sharing with retail clients
‘’ See how your SaaS business can achieve the same results ‘’
