--- title: "Mayank Jain (@mayankj) | Hashnode" description: "Mayank Jain (@mayankj) writes on Hashnode. Read their latest articles and follow their work." url: "https://hashnode.com/@mayankj" --- @mayankj # Mayank Jain @mayankj · Delhi, India · Joined June 2026 ### [Understanding BigQuery Datastream Staleness: The Freshness-vs-Cost Knob Nobody Reads the Docs On](https://syntax-soul.hashnode.dev/understanding-bigquery-datastream-staleness-the-freshness-vs-cost-knob-nobody-reads-the-docs-on?utm_source=hashnode&utm_medium=feed) If you've ever set up a Datastream pipeline replicating a transactional database (PostgreSQL, MySQL, Oracle, SQL Server) into BigQuery and then wondered why your "real-time" data is actually 10-15 min 5 min read · [syntax-soul.hashnode.dev](https://syntax-soul.hashnode.dev/understanding-bigquery-datastream-staleness-the-freshness-vs-cost-knob-nobody-reads-the-docs-on?utm_source=hashnode&utm_medium=feed) [Aug 12](https://hashnode.com/posts/understanding-bigquery-datastream-staleness-the-freshness-vs-cost-knob-nobody-reads-the-docs-on/6a7c94083bf16d911331e475) ### [Artifact Registry Cost Optimization: Tricks That Actually Move the Needle](https://syntax-soul.hashnode.dev/artifact-registry-cost-optimization-tricks-that-actually-move-the-needle?utm_source=hashnode&utm_medium=feed) If you're running container workloads on Google Cloud, there's a good chance Artifact Registry is quietly costing you more than it should. Storage adds up fast when every CI run pushes a new image, an 7 min read · [syntax-soul.hashnode.dev](https://syntax-soul.hashnode.dev/artifact-registry-cost-optimization-tricks-that-actually-move-the-needle?utm_source=hashnode&utm_medium=feed) [Jul 20](https://hashnode.com/posts/artifact-registry-cost-optimization-tricks-that-actually-move-the-needle/6a5d9f7f2d005a0c747a694e) ### [Demystifying PgBouncer: Connection Pools, Hidden Math, and Multi-Pod Scaling](https://syntax-soul.hashnode.dev/demystifying-pgbouncer?utm_source=hashnode&utm_medium=feed) If you are running PostgreSQL or AlloyDB in a high-traffic production environment, you have likely heard that you need PgBouncer. But while setting it up can seem as simple as dropping a lightweight p 10 min read · [syntax-soul.hashnode.dev](https://syntax-soul.hashnode.dev/demystifying-pgbouncer?utm_source=hashnode&utm_medium=feed) [Jul 13](https://hashnode.com/posts/demystifying-pgbouncer/6a547b4a0dfa91021504ec4a) ### [Redis in Production: Pitfalls, Anti-Patterns, and Hard-Won Lessons](https://syntax-soul.hashnode.dev/redis-in-production-pitfalls-anti-patterns-and-hard-won-lessons?utm_source=hashnode&utm_medium=feed) This is the practical, "things that actually bite people" post. Everything here is a pattern that looks fine in development, passes code review, and then causes a real incident once it hits production 9 min read · [syntax-soul.hashnode.dev](https://syntax-soul.hashnode.dev/redis-in-production-pitfalls-anti-patterns-and-hard-won-lessons?utm_source=hashnode&utm_medium=feed) [Jul 11](https://hashnode.com/posts/redis-in-production-pitfalls-anti-patterns-and-hard-won-lessons/6a51a574d3073a7ae48225da) ### [Sharding, Replication, and Sharded Replication in Redis](https://syntax-soul.hashnode.dev/sharding-replication-and-sharded-replication-in-redis?utm_source=hashnode&utm_medium=feed) verything so far has assumed a single Redis instance. That's fine for a lot of use cases, but it has two hard limits: your dataset can't be bigger than one machine's RAM, and if that one machine goes 11 min read · [syntax-soul.hashnode.dev](https://syntax-soul.hashnode.dev/sharding-replication-and-sharded-replication-in-redis?utm_source=hashnode&utm_medium=feed) [Jul 11](https://hashnode.com/posts/sharding-replication-and-sharded-replication-in-redis/6a51a4e956d3e49909261961)