This paper discusses implementation techniques for main memory databases, focusing on access methods, join algorithms, and recovery mechanisms. The authors analyze the performance of B+-trees and AVL trees for main memory databases, finding that B+-trees are preferred unless more than 80-90% of the database fits in main memory. Hash-based query processing strategies are also found to be advantageous for large memory situations. The paper evaluates various algorithms for relational database operations, including sort-merge, hash, GRACE, and hybrid hash join algorithms. It concludes that the hybrid hash algorithm is preferable over others for a wide range of parameter values. The study also discusses access planning and query optimization, noting that algorithms based on hashing are the fastest when large amounts of main memory are available. Recovery mechanisms for large memory databases are also discussed, highlighting the importance of log management and checkpointing. The paper concludes that B+-trees remain the preferred access method for keyed access to tuples in a relation unless a large portion of the database can be kept in main memory. It also notes that the results of the study apply to both large and small main memory environments. Future research directions include buffer management strategies, the impact of virtual memory on query processing, and concurrency control.This paper discusses implementation techniques for main memory databases, focusing on access methods, join algorithms, and recovery mechanisms. The authors analyze the performance of B+-trees and AVL trees for main memory databases, finding that B+-trees are preferred unless more than 80-90% of the database fits in main memory. Hash-based query processing strategies are also found to be advantageous for large memory situations. The paper evaluates various algorithms for relational database operations, including sort-merge, hash, GRACE, and hybrid hash join algorithms. It concludes that the hybrid hash algorithm is preferable over others for a wide range of parameter values. The study also discusses access planning and query optimization, noting that algorithms based on hashing are the fastest when large amounts of main memory are available. Recovery mechanisms for large memory databases are also discussed, highlighting the importance of log management and checkpointing. The paper concludes that B+-trees remain the preferred access method for keyed access to tuples in a relation unless a large portion of the database can be kept in main memory. It also notes that the results of the study apply to both large and small main memory environments. Future research directions include buffer management strategies, the impact of virtual memory on query processing, and concurrency control.