#Parquet format
18 related articles
LTAP Architecture Deep Dive: Storing P…
·3 min
LTAP Architecture Deep Dive: Storing Postgres Data in Parquet Format on S3
A deep dive into LTAP architecture: storing Postgres data in Parquet columnar format on S3 for compute-storage separation, lower costs, and unified transactional and analytical workloads.
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·3 min
DuckLake Time Travel: Version Rollback and Snapshot Queries for a Lightweight Data Lake
Explore DuckLake's time travel feature for lightweight data lakes—how snapshot-based version rollback enables data auditing, error recovery, and historical analysis, compared with Iceberg and Delta Lake.
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·3 min
DuckLake Time Travel: Version Rollback and Snapshot Queries for a Lightweight Data Lake
Explore DuckLake's time travel feature for lightweight data lake version rollback and snapshot queries, with comparisons to Iceberg and Delta Lake.
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·3 min
Flyte Deep Dive: A Practical Guide to Choosing Your ML Workflow Orchestration Tool
Deep dive into Flyte's core capabilities: cloud-native GPU scheduling, intelligent caching, checkpoint recovery, and conditional deployment — plus a full comparison with Argo and KubeFlow Pipelines.
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·3 min
Snowflake ML StandardScaler Error: 'does not index into the dataset' — A Complete Troubleshooting Guide
Fix Snowflake ML StandardScaler's 'does not index into the dataset' error. Learn why Snowflake's identifier case-folding causes column name mismatches and how to resolve them in 3 steps.
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·3 min
Decoding Databricks' AI Strategy: The Omnigents Orchestration Platform and LTAP Unified Storage Architecture
An in-depth look at the AI strategy of Databricks co-founders Matei Zaharia and Reynold Xin: the open-source Agent platform Omnigents, the unified storage architecture LTAP, and how Dream Engine reshapes data and intelligence.
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·3 min
Getting Started with Pandas: How to Choose Tutorials and Efficient Practice Resources
Struggling to pick a Pandas tutorial? This article breaks down the logic for choosing new vs. old versions, recommends hands-on resources like Kaggle and GitHub, and offers a 'tutorial + practice + projects' method to master data processing.
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·5 min
5 Things You Must Do Before Deploying AI Agents to Production (With a Banking POC Case Study)
Over 60% of AI Agent projects die between demo and production. This article breaks down Databricks lead Sandy's five-pillar methodology and a bank POC case study to help you avoid the most common deployment pitfalls.
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·7 min
The Five Pillars of Production-Grade AI Agents: A Battle-Tested Guide from Demo to Deployment
Databricks tech lead Sandy shares a five-pillar framework for production-grade AI Agents—evaluation, observability, data foundation, orchestration, and governance—with a £85K retail banking failure case to bridge the demo-to-production gap.
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·7 min
Complete Guide to Training Small Models on Kaggle's Free Compute: GPU Quotas and Practical Tips
In-depth guide to Kaggle's free-tier compute: P100/T4 GPU with 30 hours/week quota, 12-hour sessions, suitable models like CNN and BERT fine-tuning, plus tips like mixed precision and checkpointing to start deep learning at zero cost.
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·6 min
Deploying Enterprise AI Agents to Production: The Five Pillars from Demo to Launch
A Databricks expert breaks down the complete methodology for taking AI Agents from demo to production, covering the five pillars of evaluation, observability, data foundation, multi-Agent orchestration, and AI governance, with a real eight-week banking chatbot POC case.
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·7 min
Geosql: A Vertical Skill Pack That Teaches AI Geospatial Data Analysis
Geosql is a geospatial SQL skill pack designed for AI coding assistants like Claude and Codex, enabling LLMs to accurately generate PostGIS queries and handle coordinate transformations and spatial analysis.
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·7 min
Learning Python Web Scraping from Scratch: How It Works, the Full Workflow, and Legal Boundaries
A must-read intro to Python web scraping: from HTTP requests and HTML parsing to data storage, systematically explaining how crawlers work and their full workflow, while clarifying legal boundaries like the robots protocol and privacy protection.
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·3 min
WASM for Data Processing: Can Browsers Really Handle Big Data?
Can WASM really handle big data? This deep dive covers DuckDB-WASM's in-browser SQL capabilities, edge data processing architectures, and where WebAssembly fits in modern data engineering.
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Product Reviews·3 min
6 Developer Tools Roundup: AI Coding Cost Tracking, Agent Virtual File Systems, and More
Roundup of 6 developer tools: CodeBurn for AI coding token cost tracking, Mirage virtual file system for Agents, Boring SSH tunnel manager, PeerTrace file tree renderer, DataTab font-based data visualization, and Flu TypeScript Agent framework.
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Product Reviews·2 min
Milvus 3.0-beta Deep Dive: Ten Core Features and the Complete Architecture Overhaul
Deep dive into Milvus 3.0-beta's ten core features: External Collection zero-copy queries, Snapshot read-write isolation, Order By aggregation, entity-level TTL, Storage V3 engine, and more.
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Industry Insights·3 min
Deep Dive into LangChain's Full-Lifecycle Toolchain for Agent Development
LangChain unveils a full-lifecycle toolchain for Agent development at Interrupt, covering Deep Agents 0.6, SmithDB, Context Hub, LLM Gateway, and LangSmith Engine.
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Product Reviews·3 min
Datus-agent: An AI-Native CLI Tool Reshaping Data Engineering with Context Engineering
Deep dive into Datus-agent, an open-source AI-native CLI SQL client that brings Context Engineering to data engineering with natural language queries and modern data stack support.
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