Database Migration & Cost Optimization: Slashing TCO by 70% & Maximizing Performance per Dollar

Enterprise teams often find themselves trapped in escalating database bills: - **Oracle & SQL Server Licensing**: Core-based licensing fees, annual maintenance fees (often 22% of license cost annually), and restrictive virtualization rules create unsustainable annual budgets. - **Managed Cloud Overspending (AWS Aurora, DynamoDB, Snowflake)**: Serverless and managed database units charge steep premiums on IOPS, compute, and data scanning. Analytical queries in Snowflake or BigQuery running repeatedly on unchanging datasets burn tens of thousands of dollars per month. - **Performance Ceiling & CPU Bloat**: Row-based RDBMS engines handling heavy analytical aggregation struggle with latency, requiring ever-larger virtual machines with high RAM/vCPU allocations just to keep query times tolerable.

i26 designs a phased, multi-tier database migration strategy tailored to your access patterns: 1. **OLTP Workloads -> Hardened PostgreSQL & TiDB**: - For transactional systems on Oracle/MSSQL, we migrate schemas, stored procedures, and tables to PostgreSQL (or distributed TiDB / Citus for multi-terabyte scale). - Leverage PgBouncer connection pooling, JIT compilation, and partitioned table indexing to achieve sub-millisecond p99 latency on commodity cloud compute. 2. **Analytical & Timeseries Workloads -> ClickHouse & DuckDB**: - Replace costly data warehouse warehouses (Snowflake, Redshift) with ClickHouse clusters or embedded DuckDB nodes reading compressed S3 Parquet. - Vectorized query execution achieves 10x–50x speedups on aggregations while cutting RAM and CPU requirements by over 75%. 3. **Caching & Key-Value -> Valkey & ScyllaDB**: - Replace expensive Redis Enterprise and DynamoDB on-demand tables with open-source Valkey (the high-performance Linux Foundation fork of Redis) and ScyllaDB (C++ reimplementation of Cassandra/DynamoDB).

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