Aerospike’s Post

A great read to better understand how #Aerospike Graph works internally and what went into ensuring it delivers high performance and scalability, leveraging a combination of the Apache Tinkerpop framework and Aerospike's own high performance, scalable database. A lot of work went into creating custom traversal strategies, indices and custom ID structure and it shows. It's a must try graph database. You get a free 60 day trial to witness its prowess - and you can claim a 60 day trial of G.V() along with it to accelerate your graph journey and create intuitive graph visualisations for your stakeholders. What's not to like?

#Aerospike Graph provides high performance, scalability, and security. Learn more about its key features, which ensure efficient data management, dynamic query optimization, and secure access control, making it an optimal choice for enterprise #graph #database applications.

#Aerospike Graph provides high performance, scalability, and security. Learn more about its key features, which ensure efficient data management, dynamic query optimization, and secure access control, making it an optimal choice for enterprise #graph #database applications.

#Aerospike Graph provides high performance, scalability, and security. Learn more about its key features, which ensure efficient data management, dynamic query optimization, and secure access control, making it an optimal choice for enterprise #graph #database applications.

Aerospike Graph implements and adds sophisticated customizations to the Apache TinkerPop graph computing framework tailored for the #Aerospike Database. Learn about key components of its architecture and design that provide high performance and independent scalability for #graph query processing.

Aerospike Graph implements and adds sophisticated customizations to the Apache TinkerPop graph computing framework tailored for the #Aerospike Database. Learn about key components of its architecture and design that provide high performance and independent scalability for #graph query processing.

𝐇𝐨𝐰 𝐂𝐚𝐜𝐡𝐞𝐬 𝐂𝐚𝐧 𝐅𝐚𝐢𝐥 𝐚𝐧𝐝 𝐇𝐨𝐰 𝐭𝐨 𝐂𝐨𝐫𝐫𝐞𝐜𝐭 𝐓𝐡𝐞𝐦 Caching is a critical component for enhancing application performance, but it’s not without its pitfalls. Here’s a quick overview of common cache problems and their solutions: 𝐓𝐡𝐮𝐧𝐝𝐞𝐫 𝐇𝐞𝐫𝐝 𝐏𝐫𝐨𝐛𝐥𝐞𝐦: Occurs when a large number of keys expire simultaneously, leading to multiple concurrent queries hitting the database. Solution: Set random expiry times and allow only core data to hit the database. 𝐂𝐚𝐜𝐡𝐞 𝐏𝐞𝐧𝐞𝐭𝐫𝐚𝐭𝐢𝐨𝐧: Happens when non-existent keys continuously trigger cache misses, resulting in repeated database queries. Solution: Leverage a bloom filter to immediately return results for non-existent keys and cache empty results. 𝐂𝐚𝐜𝐡𝐞 𝐁𝐫𝐞𝐚𝐤𝐝𝐨𝐰𝐧: Arises when a frequently accessed hot key expires, causing a surge of queries to the database. Solution: Avoid setting expiry times for hot keys. 𝐂𝐚𝐜𝐡𝐞 𝐂𝐫𝐚𝐬𝐡: Manifests when the cache server goes down, leading to a large number of database queries. Solution: Implement circuit breakers and use a highly-available cache cluster. Effective cache management can significantly improve system performance and reliability. Be proactive in addressing these potential issues to maintain a robust and efficient application architecture. #Caching #AI #ML #EnterpriseArchitecture #DataScience #PerformanceOptimization

Aerospike Graph implements and adds sophisticated customizations to the Apache TinkerPop graph computing framework tailored for the #Aerospike Database. Learn about key components of its architecture and design that provide high performance and independent scalability for #graph query processing.

📄 Plaintext is not a great format for (system) logs #Logging #Metadata #Plaintext #Observability #Debugging https://bit.ly/4cpCOUL

If you follow me on LinkedIn, you probably hear me talk a lot about domain-specific computing and its benefits over legacy software-based search databases. Here is why: 1. It is one of the core elements of Hyperspace's solution that enables our clients to enjoy data retrieval in unprecedented ways. 2. The market demands better solutions to manage the unprecedented data workloads we are facing. Today, I'd like to focus on one of the key benefits of domain-specific computing: fast memory access. Hyperspace's proprietary search processing unit (SPU) and advanced data structures allow prefetching of all required data into the SPU before use, therefore, avoiding cache misses. This architecture overcomes the lack of control in software-based workloads, which do not have tight control over the caches and use unoptimized LRU mechanisms. Interested in learning more?https://lnkd.in/dRmz2VQ2 #elasticsearch #lexicalsearch #keywordsearch #database #search #dataretreival #vectorsearch #hybridsearch