3 个仓库
Awesome GitHub RepositoriesPostgreSQL Data Sinks
Components for storing observability data in PostgreSQL databases with batching and delivery guarantees.
Distinct from PostgreSQL Vector Stores: Distinct from PostgreSQL Vector Stores: focuses on general observability data storage rather than vector-specific extensions.
Explore 3 awesome GitHub repositories matching data & databases · PostgreSQL Data Sinks. Refine with filters or upvote what's useful.
Awesome PostgreSQL Data Sinks GitHub Repositories
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- vectordotdev/vector
vectordotdev/vector
22,071在 GitHub 上查看Vector is a high-performance observability data pipeline designed to collect, transform, and route logs, metrics, and traces across distributed infrastructure. It functions as a modular engine that decouples data ingestion from processing and transmission, utilizing a component-based architecture to connect diverse sources to multiple destinations. The project distinguishes itself through a focus on reliability and flow control. It implements backpressure-aware data movement to prevent data loss during traffic spikes and utilizes disk-backed event buffering to ensure durability during network
Writes logs, metrics, and traces into PostgreSQL databases using configurable batching and delivery guarantees.
Rusteventsforwarderhacktoberfest - arize-ai/phoenix
Arize-ai/phoenix
8,605在 GitHub 上查看Arize Phoenix is an LLM observability platform and evaluation framework designed to capture execution traces and monitor large language model applications. It serves as a prompt management system for versioning and testing templates, and as a self-hosted AI operations infrastructure for managing telemetry and experiments. The platform differentiates itself through a specialized embedding visualization tool used to detect data drift and optimize vector search. It provides a comprehensive evaluation suite that utilizes judge-based evaluators and ground-truth datasets to score model outputs, and
Implements PostgreSQL data sinks to store telemetry and observability data with scalable ingestion.
Jupyter Notebookagentsai-monitoringai-observability - dimitri/pgloader
dimitri/pgloader
6,295在 GitHub 上查看pgloader is a command-line tool that automates the migration of data and schema from various source databases and file formats into PostgreSQL. It combines schema discovery, parallel data pipelines, and type casting into a single, declarative workflow, using PostgreSQL's COPY protocol for high-throughput bulk loading. The tool distinguishes itself by compiling a dedicated command language into concurrent reader-writer pipelines that handle schema introspection, data transformation, and error-resilient batch processing. It supports migrating entire databases from MySQL, MS SQL, SQLite, and Pos
Automates migration of SQLite databases into PostgreSQL with schema discovery and index creation.
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