01
Data Storage Formats
Why CSV, JSON, and Parquet all coexist in real pipelines: file size, read speed, and tool compatibility rarely peak in the same format.
- csv
- json
- parquet
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Updated May 4, 2026 Section 1 of 9
Storage and Streaming
Storage formats, streaming, object stores, relational databases.
6 items in this section.
Long reads
02
Data Streams: Kafka and Protobuf
Kafka as a distributed log for streaming data transport, and Protobuf as a compact binary serialization format — how each works, when to use them, and why they pair well together.
- kafka
- protobuf
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Updated May 4, 2026 03
Object Storage
Covers the object storage model — buckets, keys, versioning, lifecycle policies — and Minio as a self-hosted S3-compatible implementation.
- object-storage
- s3
- minio
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Updated May 4, 2026 04
Relational Databases
A practitioner's overview of PostgreSQL: how it handles concurrency (MVCC), its type system, index types, and the Python tooling stack for working with it.
- relational-databases
- postgresql
- sqlalchemy
- alembic
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Updated May 4, 2026 Shorts
Shorts
Parquet vs CSV: Why Columns Beat Rows for Analytics
The same data, two layouts on disk. For analytical queries that touch a few columns out of many, Parquet reads tens of times less from disk than CSV — and that gap is structural, not a benchmark artifact.
- storage
- parquet
- csv
- columnar
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Jun 7, 2026 Shorts
Kafka Partitions and Consumer Groups: Where Parallelism Lives
Partition count is the ceiling on parallel consumption. Ordering is a per-partition guarantee, not a per-topic one. Two facts that decide most Kafka architecture questions.
- kafka
- streaming
- distributed-systems
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Jun 7, 2026