Startwithpg

Zarządzanie bazami danych i DBaaS

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This framework emphasizes using a relational database system as a versatile core component for building scalable, reliable data-driven applications by providing modules and guides that facilitate features such as durable queues, search indexing, job scheduling, and flexible extensions, thereby reducing unnecessary architectural complexity. It addresses common challenges like over-distribution and premature system fragmentation by promoting deep utilization of the database's native capabilities before adding specialized infrastructure, making it ideal for developers designing new systems who seek to maintain simplicity, consistency, and maximum flexibility in data management and processing workflows.

Startwithpg można znaleźć w Database Management & DBaaS kategorie.

Produkty najbardziej podobne do Startwithpg to:

Taskade Lansowany → Price, Bergnaum and Watsica Ultimate Lansowany → YDB → ABP → StatelyDB →

Zrzuty ekranu

Bliższe dane

Startwithpg Główne cechy

• Pick a module
  Choose the part of the system you want to build and follow the setup guides for it.
• Compare systems
  Choose the right tool by comparing options, not by adding many tools at once.
• Start with Postgres
  Use Postgres as your first database because it handles many tasks well before needing more complex systems.
• Use Postgres deeply
  Use Postgres thoroughly and only add other tools when necessary as evidence shows.
• BOOT: plain postgres
  Start with plain Postgres for initial setup.
• Moving parts avoided
  Avoid adding new systems unless really needed, to keep the system simple.
• Instead of Kafka pgmq
  Use pgmq for simple jobs and event handling instead of starting with Kafka.
• HOLD: one source of truth
  Keep one main database (Postgres) as the main source of truth for your data.
• Writes Queues Search Jobs
  Use Postgres for writing data, queues, searching, and job management in the beginning.
• Use JSONB instead of MongoDB
  Use JSONB in Postgres for parts of your data that change often but still need SQL features.
• Use pgvector instead of Vector DB
  Use pgvector for early search needs that use product data and filters.
• Default database / maximum optionality
  Start with Postgres by default to keep the system simple and flexible.
• LOAD: extensions when evidence appears
  Add special features or extensions to Postgres only when you see a clear need for them.
• Route the first version through Postgres
  Build the first version of your system using Postgres first.
• Use TimescaleDB instead of Time-series DB
  Use TimescaleDB when your time-based data is part of your main data and SQL is enough.
• Strong defaults, real caveats, and graduation signals
  Use good default settings and watch for signs when it’s time to change or add new tools.
• Most systems do not fail because Postgres was not powerful enough
  Problems usually happen not because Postgres can't handle the work, but because the system became too complex too early.

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