Lakebase — Learn free · DataAI Nexus

Self-check

Questions 1–10 of 10

1. In which established class of systems is the conceptual foundation of Lakebase rooted?
Question 1A. HTAP (Hybrid Transactional/Analytical Processing)B. Mainframe batch processingC. Flat-file storageD. Spreadsheet softwareE. Content management systems
2. Which of the following is NOT one of the modernised architectural elements that Lakebase introduces?
Question 2A. Decoupled compute and storageB. Tightly coupled compute and storageC. Metadata-as-control-plane executionD. Branchable workloads and snapshot isolationE. AI-native compatibility and elastic serverless scaling
3. Which three siloed tool categories are described as having shackled enterprises for decades before Lakebase?
Question 3A. Email, spreadsheets and word processorsB. Web servers, DNS and firewallsC. OLTP systems for transactions, OLAP platforms for analytics and AI/ML stacks operating in isolationD. Data marts, data warehouses and data lakesE. Backups, archives and cold storage
4. What storage does Lakebase use, in contrast to the proprietary or row-store storage of traditional HTAP?
Question 4A. Plain CSV filesB. In-memory tables onlyC. A proprietary row storeD. Delta Tables (columnar, transactional)E. Tape archives
5. How is governance handled in Lakebase, compared with traditional HTAP?
Question 5A. Governance is left to each applicationB. Governance is engine-bound and limitedC. There is no governance layerD. Governance is handled by manual spreadsheetsE. Governance is metadata-first via Unity Catalog
6. What does Lakebase transform metadata into?
Question 6A. An active, decision-making layer rather than passive documentationB. A read-only archiveC. A billing statementD. A backup of the dataE. A user manual
7. In the Lakebase architectural flow, what API does the application use to connect?
Question 7A. A proprietary binary protocolB. A Postgres-compatible APIC. A spreadsheet plug-inD. An FTP endpointE. A mainframe terminal
8. In the FinTech fraud detection comparison, which components did the Lakebase approach use?
Question 8A. TiDB for ingestion and a local cacheB. SAP HANA for combined processingC. Branch-per-session design for scoring, PgVector for embeddings, Delta Lake for storage and Unity Catalog for governance and lineageD. A single monolithic HTAP engineE. Manual spreadsheets for scoring
9. In the telecom data monetisation example, what outcome followed the upgrade from SAP HANA to Lakebase?
Question 9A. Increased vendor lock-inB. A 30% increase in costsC. No measurable changeD. A 30% cost reduction and improved service agilityE. The removal of all AI capabilities
10. Which statement reflects why Lakebase matters as businesses move toward federated data platforms and autonomous systems?
Question 10A. Metadata should be ignored in favour of raw dataB. Real-time agents need no snapshotsC. Workloads should each have their own separate source of truthD. Analytics and transactions must remain in separate systemsE. Metadata is the control plane, real-time agents require rollback-ready snapshots, and workloads span dashboards, models, APIs and pipelines from a single source of truth