Shiv Iyer (@thewebscaledba) 's Twitter Profile
Shiv Iyer

@thewebscaledba

Data Engineering | Data Analytics | Cloud & Big Data Architect | MinervaDB | ChistaDATA | OLAP | Advanced SQL | Python | ML | AI | Investor | Entrepreneur

ID: 3180496861

linkhttps://www.linkedin.com/in/thewebscaledba/ calendar_today30-04-2015 10:19:37

2,2K Tweet

1,1K Followers

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🔧 PostgreSQL Sync Replication Troubleshooting Pro Tips: ✅ Check synchronous_standby_names config ✅ Verify network connectivity between primary/standby ✅ Monitor pg_stat_replication for lag metrics ✅ Ensure wal_level = replica ✅ Validate synchronous_commit settings Quick

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🚀 Vectorized computing is revolutionizing #GenAI! From SIMD operations accelerating transformer attention mechanisms to GPU-optimized matrix multiplications in diffusion models, parallel processing is the secret sauce behind: ✨ Lightning-fast RAG with FAISS/Annoy ⚡ Real-time

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🔍 PostgreSQL's cost-based optimizer is the unsung hero of query performance! It analyzes table statistics, evaluates join algorithms, and chooses execution paths that can make your queries 100x faster ⚡ Key operations that boost performance: 📊 Statistics analysis with

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📊 Essential Cassandra metrics for bulletproof performance monitoring! 🎯 Read/Write Performance: • Read/Write latency P95/P99 percentiles • Ops/sec per table & keyspace • Pending compactions count • SSTable count per table Resource Utilization: • JVM heap usage & GC

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🚀 Scaling heterogeneous database infrastructure? DevOps efficiency is your secret weapon! 🎯 Infrastructure as Code: • Terraform modules for multi-DB deployments • Ansible playbooks for config management • Kubernetes operators for automated scaling Unified Operations: •

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⚡ Optimizing LSM write performance? Here's your playbook for scaling write-heavy workloads! 🚀 Write Path Optimization: • Batch writes to reduce WAL overhead • Tune memtable size & flush intervals • Optimize compaction strategy (leveled vs size-tiered) • Configure write

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🔍 PostgreSQL Pro Tip: Hunting down those pesky long-running queries! 🎯 Quick Investigation Steps: 1️⃣ Find the culprits: SELECT pid, query, state, query_start FROM pg_stat_activity WHERE state = 'active' AND query_start < now() - interval '5 minutes'; 2️⃣ Check execution

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The brutal reality: * 53% of users abandon apps that take >3s to load * 1 second delay = 7% conversion drop * Poor performance kills frequency before monetization even starts Day 1 Technical Imperatives: ✅ Load balancing & auto-scaling ready ✅ Database read replicas

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🎯 Redis sharding for Ad Tech? Here's how to handle 100K+ QPS with sub-millisecond latency! ⚡ Sharding Strategy for Ad Tech: • User-based sharding (consistent hashing on user_id) • Campaign-based partitioning for targeting data • Geo-based shards for location targeting

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🗃️ SQL vs NoSQL vs NewSQL: Choosing the right database for your technical use case! 🎯 SQL (RDBMS) - The Reliable Workhorse: ✅ ACID transactions & strict consistency ✅ Complex joins & analytical queries ✅ Financial systems, ERP, CRM ✅ Structured data with clear

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AI is transforming data analytics in 2025! From automated data cleaning to predictive modeling, businesses now unlock deeper, faster insights than ever before. Ready for smarter decisions? 🤖📊 #DataAnalytics #AI #MachineLearning #Innovation #BigData

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Seamless replication and instant failover in PostgreSQL keep your data safe and apps always online! 🔄🛡️ With streaming replication and automatic switchover, enjoy zero downtime and bulletproof resilience for mission-critical workloads. #PostgreSQL #Replication #Failover

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Data vectorization represents the critical preprocessing step that transforms raw, unstructured data into dense numerical representations within high-dimensional vector spaces. Modern transformer architectures rely on embedding layers that map discrete tokens (words, subwords, or

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⚡ Cassandra HA: Engineered for Zero Downtime Ring topology with consistent hashing ensures data distribution across nodes. Tunable consistency levels (ONE, QUORUM, ALL) balance performance vs. durability. Multi-datacenter replication with NetworkTopologyStrategy provides

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🗄️ DevOps Meets Database: Infrastructure as Code for Data Tier Terraform provisions DB clusters, Ansible automates configuration management, and GitOps pipelines deploy schema migrations with zero downtime. Monitoring with Prometheus, backup automation, connection pooling, and

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🔧 PostgreSQL 17 I/O Troubleshooting Tip High disk waits? Check pg_stat_io for bottlenecks, tune shared_buffers (25% RAM), enable wal_compression, set checkpoint_completion_target=0.9, and consider splitting WAL to separate SSD. Use iotop + pg_stat_statements to identify heavy

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Kafka internals and practical hacks for boosting performance and scalability: 1. Want to supercharge your Kafka cluster? 🚀 Tune `num.network.threads` and `num.io.threads` to match your CPU cores for massive gains in network and disk throughput!

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minervadb.xyz/kafka-performa… Kafka Performance Tuning – Producer Configuration and Cluster Optimization #Kafka #MinervaDB #ChistaDATA #KafkaSupport #KafkaPerformance ChistaDATA Inc. MinervaDB

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🌟 Star Schema = Data modeling genius! Facts = "what happened" (sales, clicks), Dimensions = "context" (who, when, where). Denormalized dims trade storage for speed. Your queries will thank you! 🚀 #DataEngineering #StarSchema #DataModeling #Analytics