Blogsby GlyphBuild vs. Buy: Flexible Data Pipeline Development
Build vs. buy data pipelines is more than a tooling decision. Learn about the hidden costs, trade-offs, and TCO across flexible pipelines, SaaS tools, and DIY architectures.
6 of 392 posts
Thu Feb 261 post
Fri Feb 201 post
The Vector Database Hype is Over (and That's Good)
The vector database era is fading as Postgres and PGVector absorb the capability. Learn why co-locating vectors with your primary database reduces cost and complexity, plus data engineering practices to improve AI retrieval quality.
Thu Feb 191 post
Data Movement Layer: Why Enterprises Need More Than Pipelines
Enterprises outgrow traditional data pipelines. Learn why a data movement layer delivers durable, right-time data across analytics and operations.
Thu Feb 121 post
Kafka vs. Estuary: When to Choose What
Compare Kafka vs Estuary across architecture, CDC, performance, and total cost of ownership to decide which platform fits your real-time data needs.
Tue Feb 101 post
Throughput vs Latency: Understanding the Key Difference in Data Engineering
Understand latency vs throughput, how Little’s Law links them via work in progress, and how to balance responsiveness and scale under load.
Mon Feb 91 post
Monitoring Snowflake Pipelines with Estuary’s OpenMetrics API
Learn how to monitor Snowflake pipelines using Estuary’s OpenMetrics API. Track throughput, errors, and latency with Prometheus and Grafana.