While RAM is indeed orders of magnitude faster than disk storage (nanosecond vs. millisecond access times), database systems require a balanced approach:

-- Example showing memory-hungry vs. disk-intensive operations
-- Memory-bound query (works well with large RAM):
SELECT * FROM cached_data WHERE id IN (SELECT id FROM lookup_table);

-- Disk-bound query (benefits from fast storage):
SELECT * FROM large_table ORDER BY non_indexed_column;

• Working Set Limitations: Not all data is active simultaneously. The "working set" (frequently accessed data) might only be 20-30% of total DB size.
• Write Operations: RAM can't permanently persist changes - all writes must eventually hit disk
• Checkpoint Operations: SQL Server's checkpoint process writes dirty pages to disk regardless of RAM size

Here's a practical configuration example for a 500GB database:

-- Recommended memory configuration (SQL Server example)
EXEC sp_configure 'max server memory', 64000; -- 64GB for 500GB DB
GO
RECONFIGURE;
GO

-- Accelerate tempdb (critical for sorting/hashing)
ALTER DATABASE tempdb MODIFY FILE (NAME = tempdev, SIZE = 8GB);

A balanced deployment might look like:

-- Modern infrastructure example
1. 64-128GB RAM for buffer pool
2. NVMe storage for transaction logs
3. RAID 10 SSD array for data files
4. Slower archive storage for backups

Use these DMVs to check your actual memory pressure:

SELECT
    physical_memory_kb/1024 AS [Physical RAM (MB)],
    committed_kb/1024 AS [SQL Server Committed (MB)],
    committed_target_kb/1024 AS [SQL Server Target (MB)]
FROM sys.dm_os_sys_memory;

SELECT TOP 10
    DB_NAME(database_id) AS [Database],
    COUNT(*) * 8/1024 AS [Cached Size (MB)]
FROM sys.dm_os_buffer_descriptors
GROUP BY database_id
ORDER BY [Cached Size (MB)] DESC;

This approach gives you the best balance between RAM's speed and disk's persistence, while being cost-effective for most workloads.

When considering SQL Server performance optimization, the fundamental equation balances RAM capacity against storage speed. While both play crucial roles, they address different aspects of database operations:

-- Example showing memory-hungry query
SELECT * FROM large_table 
WHERE complex_condition = true 
ORDER BY multiple_columns
-- This benefits more from RAM

While your suggestion of loading 100GB RAM seems logical, several technical constraints apply:

• Working Set Size limitations in SQL Server's buffer pool
• Memory pressure from other system processes
• NUMA architecture constraints in multi-socket servers

-- Check current memory allocation
SELECT
    physical_memory_kb/1024 AS [Physical Memory (MB)],
    committed_kb/1024 AS [SQL Server Committed (MB)],
    committed_target_kb/1024 AS [Target Committed (MB)]
FROM sys.dm_os_sys_memory;

RAM primarily accelerates read operations. For write-heavy workloads, storage speed becomes critical:

-- Transaction log writes can't be cached indefinitely
BEGIN TRANSACTION
UPDATE massive_table 
SET frequently_changed_column = new_value
WHERE business_critical_condition = true
-- This requires durable storage commit

Optimal setups vary by workload. Here are real-world scenarios:

When maximizing RAM utilization, consider these SQL Server features:

-- Enable Buffer Pool Extension (uses SSD as memory extension)
ALTER SERVER CONFIGURATION 
SET BUFFER POOL EXTENSION ON 
(FILENAME = 'F:\SSD_Cache\BP_Extension.bpe', SIZE = 50GB);

-- Configure memory for columnstore indexes
EXEC sp_configure 'show advanced options', 1;
RECONFIGURE;
EXEC sp_configure 'columnstore memory limit', 4096; -- MB
RECONFIGURE;

For budget-conscious deployments, these strategies balance cost/performance:

• Use RAM for active working set + SSD caching
• Implement delayed durability for non-critical writes
• Leverage memory-optimized tempdb

-- Create memory-optimized temp table
CREATE TABLE #temp_inmem (
    id INT PRIMARY KEY NONCLUSTERED,
    data NVARCHAR(MAX)
) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_ONLY);

These queries help evaluate your memory/storage balance:

-- Check page life expectancy (indicator of memory pressure)
SELECT [object_name], cntr_value AS [Page Life Expectancy]
FROM sys.dm_os_performance_counters
WHERE [object_name] LIKE '%Buffer Manager%'
AND counter_name = 'Page life expectancy';

-- Identify disk-bound queries
SELECT TOP 10
    qs.total_logical_reads/qs.execution_count AS avg_logical_reads,
    qs.total_elapsed_time/qs.execution_count AS avg_elapsed_time,
    SUBSTRING(qt.text, (qs.statement_start_offset/2)+1,
        ((CASE qs.statement_end_offset
          WHEN -1 THEN DATALENGTH(qt.text)
         ELSE qs.statement_end_offset
         END - qs.statement_start_offset)/2) + 1) AS query_text
FROM sys.dm_exec_query_stats AS qs
CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) AS qt
ORDER BY avg_logical_reads DESC;