OLTP (Online Transaction Processing)

Key Characteristics

• ▶Optimize for rapid execution of small, focused transactions
• ▶Access individual or small sets of records via primary keys
• ▶Require strong consistency guarantees (ACID properties)
• ▶Support high concurrency with isolation between transactions
• ▶Use row-oriented storage and B-tree indexes
• ▶Normalized schemas to minimize redundancy and update costs

Why It Matters

• ▶Enable reliable operational systems handling millions of daily transactions
• ▶Ensure data consistency for critical business operations
• ▶Maintain availability for user-facing applications
• ▶Provide responsiveness (sub-second latency) for interactive use
• ▶Support concurrent operations without corruption or data loss
• ▶Scale to handle peak transaction volumes

Example

`
-- OLTP transaction: Process e-commerce purchase

BEGIN TRANSACTION;

-- 1. Insert order
INSERT INTO orders (customer_id, order_date, status)
VALUES (12345, NOW(), 'pending')
RETURNING order_id;

-- 2. Update inventory
UPDATE products 
SET quantity_on_hand = quantity_on_hand - 5
WHERE product_id = 789 AND quantity_on_hand >= 5;

-- 3. Record payment
INSERT INTO payments (order_id, amount, method, status)
VALUES (50001, 99.99, 'credit_card', 'processed');

-- 4. Update customer profile
UPDATE customer_profiles
SET last_purchase_date = NOW(),
    lifetime_value = lifetime_value + 99.99
WHERE customer_id = 12345;

COMMIT;

-- All operations succeed atomically or all rollback
-- Isolation ensures other transactions see consistent state
-- Indexes on customer_id, product_id, order_id accelerate lookups
`

Coginiti Perspective

While Coginiti is focused on analytical workloads rather than OLTP, it connects to OLTP systems (Aurora, RDS, Cloud SQL, AlloyDB, Azure SQL, SQL Server, Oracle) as data sources. CoginitiScript pipelines can extract from these operational databases and publish transformed results to analytical platforms using incremental strategies. This ELT pattern keeps OLTP systems dedicated to transactional performance while making their data available for analysis without additional tooling.

Related Concepts