Data warehouse migrations are high-risk: 18-month projects, 6-figure budgets, business-critical downtime. NKKTech ships zero-downtime migration via CDC + dual-write patterns for Redshift → Snowflake, on-prem → BigQuery, Synapse → Snowflake, legacy ETL → Databricks Lakehouse. Fixed-scope from USD 60K. Singapore-law MSA, ISO 9001 + ISO 22301 certified.
Five migration patterns we run most often. Every migration follows the same risk-reduction playbook: parallel-run validation, dual-write cutover window, rollback plan tested before go-live.
Our most-common migration. SQL dialect translation (Redshift → Snowflake idioms), workload re-tuning (Snowflake's warehouse model differs from Redshift's node model), BI tool reconnection. Zero-downtime via dual-write window. Engagement: USD 60K (small <1TB) to USD 280K (enterprise multi-TB with 100+ data sources).
Lift-and-shift OR re-architect during migration (we recommend the latter). Includes Teradata, Oracle Exadata, SQL Server, Netezza source compatibility. CDC tooling: Datastream (BigQuery), Snowpipe + CDC, Databricks Auto Loader. 4-8 month engagement typical for enterprise multi-TB workloads.
Common pattern when Azure-mandate is lifted or cost optimization drives change. Synapse SQL → Snowflake SQL dialect translation, Polybase external table → Snowflake external table conversion, Azure Data Factory pipelines → Snowpipe/Tasks. Workload re-tuning for Snowflake's warehouse model.
Re-platform from Informatica / Talend / SSIS / DataStage to Databricks Lakehouse with Delta Lake. Often paired with adopting Unity Catalog for governance. We retain business logic (>95% test coverage) while modernizing the runtime. Common driver: ETL tool licensing costs + skills shortage.
AWS Redshift → GCP BigQuery, or vice versa. Often driven by procurement change (parent company AWS shift, EU sovereignty mandate, vendor consolidation). Same risk-reduction playbook: parallel-run, dual-write cutover, validated rollback. Cross-cloud egress costs estimated upfront.
Pre-engagement audit: catalog source warehouse (size, table count, query patterns, BI tool dependencies), recommend target + architecture, estimate budget + timeline within ±20%. Output: a written scoping document procurement can review. Most clients engage us for the full migration after this audit.
Senior architect joins. Discuss source + target, business drivers, must-have-by dates, downtime tolerance. Outcome: recommend either scoping engagement OR direct go-ahead for migration.
Catalog source warehouse, recommend target, budget + timeline estimate within ±20%. Written scoping document. Reviewable by your CTO + procurement.
Phases: (1) replicate schema + sample data on target, (2) parallel-run with CDC dual-write window, (3) validation + BI tool reconnect, (4) cutover at low-traffic window, (5) rollback plan tested but unused. Milestone-based payment.
Cutover at agreed low-traffic window. We stay on-call for first 30 days post-cutover (warranty included). Then optional retainer for ongoing warehouse ownership: USD 8-25K/month.
Compliance-aware migration: audit-trail preservation (no lost transactions during cutover), regulator-pre-approved cutover windows, full reconciliation reports between source + target. Engagement USD 180-400K typical for regulated mid-tier banks.
Startup pattern: outgrew Postgres analytics queries, migrating to Snowflake or BigQuery. Often combined with Segment/Rudderstack adoption + dbt project bootstrap. USD 60-120K typical, 6-10 weeks.
Pattern: legacy Teradata/Netezza warehouse for inventory + customer 360, migrating to Databricks Lakehouse for ML-readiness. USD 200-350K. Often paired with adopting Unity Catalog + dbt for transformation.
Source: on-prem SQL Server / Oracle. Target: BigQuery (with HIPAA BAA) or Snowflake (with HITRUST). De-identification re-validation during migration. BAA contracting via NKKTech Pte Ltd.
Common 2024-2026 pattern: enterprises moving off Azure Synapse to Snowflake for 30-50% TCO reduction + better multi-cloud portability. Engagement USD 100-220K typical.
Legacy time-series warehouses → Snowflake (with Iceberg) or BigQuery (with BigLake). Often paired with adopting Apache Iceberg for portable storage layer. USD 150-280K. PrismLab AI/AR Japan factory CV adjacency.
Small (<1TB, simple schema): 6-10 weeks. Medium (1-10TB, 50-100 sources): 3-5 months. Enterprise (10TB+, 200+ sources, regulated): 6-12 months. Most-time-consuming phases: source cataloging + SQL dialect translation + BI tool reconnection. Cutover itself is usually 1-2 days.
Zero downtime is achievable for most migrations via CDC + dual-write pattern. Source DB streams changes to both old + new warehouse during cutover window (typically 1-4 weeks). Validation runs on both, then BI tools point to new warehouse. Rollback plan is tested before go-live but rarely used.
Yes — Redshift→Snowflake, Synapse→Snowflake, Oracle→BigQuery, etc. Most modern translators are 60-80% automated. Remaining 20-40% requires human review (especially for complex CTEs, window functions, vendor-specific extensions). We include translation as part of migration scope.
Yes — Tableau, Looker, Power BI, Mode, Sigma, Hex, Lightdash. Connection-string update + workload-tuning (different query plans on different warehouses). Reverse-ETL via Hightouch/Census reconnection. Typically a 1-2 week task included in migration scope.
Three-layer validation: (1) Row counts + checksums on every table (Datafold). (2) Aggregate metric comparison (revenue / customer count / KPI dashboards must match within 0.01%). (3) Spot-check on highest-business-impact records. Validation runs continuously during dual-write window — we don't cutover until all 3 pass for 7+ consecutive days.
Lead architect (15+ yrs) + 2-3 senior data engineers + 0.5 FTE PM. Hanoi-based with timezone coverage for your business hours. ISO 9001 + ISO 22301 certified processes. Standard escalation path with your CTO + a named NKKTech account director (Tony or another senior).
NKKTech delivered our LLM document processing pipeline on time and exactly on budget. The tech lead was available on Slack daily. First offshore team that actually worked the way we expected.
Tony's team understood our legacy PHP system faster than our internal team. Zero downtime migration, exactly as promised. The bilingual PM made communication seamless.
We went from 15 hours/week of manual prospecting to fully automated lead gen in 8 weeks. ROI in 60 days as Tony promised.
NKKTech delivered our LLM document processing pipeline on time and exactly on budget. The tech lead was available on Slack daily. First offshore team that actually worked the way we expected.
Last updated: · Reviewed quarterly for accuracy.
30-minute free discovery call with a senior NKKTech engineer (not a sales rep). We'll review your requirements, scope an engagement, and tell you honestly whether we're the right fit.
Book your callEnd-to-end LLM, RAG, and computer vision systems for production.
Learn MoreAutonomous agents that automate work your team shouldn't be doing.
Learn MoreSenior-first AI engineering partner — Vietnam-based, globally delivered.
Learn MoreCustom autonomous agents with multi-agent orchestration.
Learn MorePre-vetted AI engineers onboard in 2 weeks at 40-60% lower cost.
Learn MoreCut manual operations 60-90% with custom AI automation.
Learn MoreProject monthly LLM API bill across GPT-4o, Claude 3.5, Gemini, self-hosted Llama. 100% client-side.
Learn More3-year TCO + payback for RAG builds. Compare pgvector, Pinecone, Weaviate, Qdrant at your workload.
Learn More10-question score across 7 readiness dimensions. Tier-based recommendations + top 3 gaps to address first.
Learn More