Aerospike’s Post

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.

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 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. https://lnkd.in/gm6Xr5vQ

#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.

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?

> When using Clean Architecture and DDD paradigms, separation of the persistence layer and the domain model layer is a primordial one. Primordial? Like, existing at or from the beginning of time; primeval? Who said so? Why? Is it because you don't know how to write SQL and program databases so you just have to download everything to memory objects? Oh, I think it is. https://lnkd.in/dy_GdZ4u

Enjoy this programming-language-agnostic kind of system design foundational template along with links to the core concepts. 👍 𝐒𝐲𝐬𝐭𝐞𝐦 𝐃𝐞𝐬𝐢𝐠𝐧 𝐊𝐞𝐲 𝐂𝐨𝐧𝐜𝐞𝐩𝐭𝐬 1. Scalability: https://lnkd.in/gpge_z76 2. Latency vs Throughput: https://lnkd.in/g_amhAtN 3. CAP Theorem: https://lnkd.in/g3hmVamx 4. ACID Transactions: https://lnkd.in/gMe2JqaF 5. Rate Limiting: https://lnkd.in/gWsTDR3m 6. API Design: https://lnkd.in/ghYzrr8q 7. Strong vs Eventual Consistency: https://lnkd.in/gJ-uXQXZ 8. Distributed Tracing: https://lnkd.in/d6r5RdXG 9. Synchronous vs. asynchronous communications: https://lnkd.in/gC3F2nvr 10. Batch Processing vs Stream Processing: https://lnkd.in/g4_MzM4s 11. Fault Tolerance: https://lnkd.in/dVJ6n3wA 👍 𝐒𝐲𝐬𝐭𝐞𝐦 𝐃𝐞𝐬𝐢𝐠𝐧 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐁𝐥𝐨𝐜𝐤𝐬 1. Databases: https://lnkd.in/gti8gjpz 2. Horizontal vs Vertical Scaling: https://lnkd.in/gAH2e9du 3. Caching: https://lnkd.in/gC9piQbJ 4. Distributed Caching: https://lnkd.in/g7WKydNg 5. Load Balancing: https://lnkd.in/gQaa8sXK 6. SQL vs NoSQL: https://lnkd.in/g3WC_yxn 7. Database Scaling: https://lnkd.in/gAXpSyWQ 8. Data Replication: https://lnkd.in/gVAJxTpS 9. Data Redundancy: https://lnkd.in/gNN7TF7n 10. Database Sharding: https://lnkd.in/gMqqc6x9 11. Database Index's: https://lnkd.in/gCeshYVt 12. Proxy Server: https://lnkd.in/gi8KnKS6 13. WebSocket: https://lnkd.in/g76Gv2KQ 14. API Gateway: https://lnkd.in/gnsJGJaM 15. Message Queues: https://lnkd.in/gTzY6uk8 👍 𝐒𝐲𝐬𝐭𝐞𝐦 𝐃𝐞𝐬𝐢𝐠𝐧 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐚𝐥 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬 1. Event-Driven Architecture: https://lnkd.in/dp8CPvey 2. Client-Server Architecture: https://lnkd.in/dAARQYzq 3. Serverless Architecture: https://lnkd.in/gQNAXKkb 4. Microservices Architecture: https://lnkd.in/gFXUrz_T 👍 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐂𝐨𝐝𝐢𝐧𝐠 𝐑𝐨𝐮𝐧𝐝 𝐚𝐧𝐝 𝐋𝐨𝐰 𝐋𝐞𝐯𝐞𝐥 𝐃𝐞𝐬𝐢𝐠𝐧 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬 1. Design a Parking Lot: https://lnkd.in/dQaAuFd2 3. Design Chess Validator: https://lnkd.in/dfAQHvN4 4. Design a Distributed Queue | Kafka: https://lnkd.in/dQ6_B4_M 5. Design Tic-Tac-Toe: https://lnkd.in/dFDApUBt PS: The diagram’s credit goes to DesignGurus.