Why Audit Trails Matter in ClickHouse®: Building Accountability, Compliance, and Security
When teams evaluate database platforms, the conversation usually revolves around performance, scalability, query optimization, and storage efficiency.…
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I Built a Mini Message Broker in Pure Python and Finally Understood How Kafka Moves Millions of Events
Last year I was on a team that pushed 40 million events per day through Kafka. We had consumer lag alerts, rebalancing incidents, and a whole runbook …
day 01 of learning data engineering (step1: sql joins and set operators)
So, yes. Today's goal is to get the 30hr SQL Bootcamp completed (or at least as much as I can), I am following Data with Baara. Who gets a 5 on 5 for …
You can do WHAT with a Kafka proxy?
At Current 2026, I realized that nobody knows exactly what a Kafka proxy can do. Most engineers and architects think it's just some kind of reverse-pr…
The Data Engineer Roadmap for 2026 (in an AI-Native World)
This is the narrated version of our free, interactive Data Engineer Roadmap . Same areas, same order, with a focus on the one thing each layer asks of…
Querying Germany's Company Register via API: Clean JSON and the new eGbR
Germany has no Companies House Unlike the UK's free official API, German company data is fragmented across regional courts and published through the H…
I Built a Consistent Hashing Ring in Pure Python and Finally Understood How Cassandra Distributes Data
I Built a Consistent Hashing Ring in Pure Python and Finally Understood How Cassandra Distributes Data I've been using Cassandra and Redis Cluster for…
From STTM to Snowflake SQL: Building a Metadata-Driven Data Engineering Copilot
Most data engineering teams do not struggle because they lack smart people. They struggle because too much of the delivery process is still repetitive…
Day 17 of #100DaysOfClickHouse: Mastering Data Filtering for Faster ClickHouse Queries
When working with ClickHouse®, writing a query is usually straightforward. Writing an efficient query, however, requires understanding how ClickHouse …
What is the best real-time analytics database in 2026? An engineering buyer's guide
Traditional databases just can't keep up with high concurrency and low latency at the same time. The term "real-time" has become kind of meaningless. …
Vertica vs VoltDB (Volt Active Data): Key Differences, Use Cases & How to Choose in 2026
If you're building a modern data stack that requires either high-throughput transaction processing or large-scale analytical workloads, you've likely …
this is scary (day 0 of learning data engineering)
apparently i need to build in public and create a personal brand to get a job, which tbh is a big big ask from little introvert me, who would rather g…
Building My First End-to-End ETL Pipeline with Airflow, BigQuery, and Docker
Recently, I completed my first full Data Engineering project: building an end-to-end ETL pipeline using real-world Australian weather data spanning 10…
AMLA Is Coming Online: What the EU's New Anti–Money Laundering Authority Means for Builders and Regulators
If you work anywhere near payments, banking, crypto, or fintech in Europe, a new acronym is about to land in your backlog: AMLA — the EU's Authority f…
SELECT FINAL and OPTIMIZE FINAL Are Not the Same Thing
One thing that confused me when I first started learning ClickHouse was the word FINAL . Because eventually you'll come across both: SELECT * FROM eve…
Why Metadata-Driven ETL Frameworks Scale Better Than Hardcoded Pipelines — and Where They Don't
Over the years, I've seen many data platforms start with good intentions. A few scripts are created to move data from one system to another, and every…
How I Cut SQL Query Time from 45 Seconds to 8 Seconds on 2.3 Million Rows
I inherited a SQL Server database with 2.3 million rows. Queries took 45 seconds. Users were frustrated. Dashboards timed out. Here is exactly what I …
How I Cut SQL Query Time from 45 Seconds to 8 Seconds on 2.3 Million Rows
I inherited a SQL Server database with 2.3 million rows. Queries took 45 seconds. Users were frustrated. Dashboards timed out. Here is exactly what I …
Linux Fundamentals for Data Engineering
Introduction As a data engineer, most of your work will happen on Linux servers. Whether you are managing databases, running data pipelines, or proces…
Apache Data Lakehouse Weekly: June 4 to June 11, 2026
The lakehouse community spent this week arguing about versions, and the arguments mattered. Parquet contributors produced the single largest thread ac…
Modern Data Stack Migration — Day 1: Scaling to 8+ Companies with DRY Architecture and Chasing a $2M Discrepancy
Hello everyone! Following up on my previous post , Day 1 of my Modern Data Stack migration was an absolute rollercoaster of refactoring and deep data …
Data Lineage Is a Vanity Metric Without Business Context
Most lineage tools produce beautiful diagrams that don't answer the one question that matters: 'What breaks if this data is wrong?' Here's how to move…
QN : Ingest and transform data in a lakehouse
lakehouse has two storage areas ; Files and Tables Files Store structured, queryable data by sql Supports schema definitions and ACID transactions Tab…
Apache Kafka Explained: A Practical Beginner Guide for Data Engineers
If you're learning data engineering, you'll probably meet Apache Kafka very early. You'll see it in job descriptions, system design diagrams, real-tim…
From Dashboards to Autonomous Action: Why You Need to Attend Google Cloud Labs
The era of passive data analytics is over. Today, the most forward-thinking data teams aren't just building dashboards to show what happened yesterday…
Linux Fundamentals for Data Engineering
When you are starting out in Data Engineering, it is easy to focus entirely on writing pristine Python code, designing SQL schemas, or learning comple…
Extract data from Databases into DuckLake
Introduction In the evolving landscape of data engineering, DuckLake is emerging as a powerful solution for building data lakes with ACID transactions…
100 Days of ClickHouse® – Day 6: Importing CSV Files into ClickHouse®
CSV files are one of the most common formats for storing and exchanging data. Whether you’re working with logs, analytics data, application exports, o…
Organizing How to Use AWS Lake Formation
Original Japanese article : AWS Lake Formationの使い方について整理してみる Introduction I'm Aki, an AWS Community Builder ( @jitepengin ). Previously, I wrote an ar…
ETL Pipeline: Fetching Real-Time News Data with Python and Postgres
The best way to actually understand data engineering is to build something that breaks, fix it, and watch it successfully run. In this article, we bui…