🔮 Instill Core is a full-stack AI infrastructure tool for data, model and pipeline orchestration, designed to streamline every aspect of building versatile AI-first applications
- unstructured-data
- low-code
- developer-tools
- etl
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🔮 Instill Core is a full-stack AI infrastructure tool for data, model and pipeline orchestration, designed to streamline every aspect of building versatile AI-first applications
The fastest unified streaming SQL Engine in a single C++ binary. ⚡ Millisecond latency. 100+ GB/s throughput. Continuously compute stateful context from streams, logs, metrics, events, and CDC.
A distributed data integration framework that simplifies common aspects of big data integration such as data ingestion, replication, organization and lifecycle management for both streaming and batch data ecosystems.
A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow
MongoDB data stream pipeline tools by YouGov (adopted from MongoDB)
高性能表格数据导出器
Data processing & ETL framework for Ruby
The ToroDB solution to provide better analytics on top of MongoDB and make it easier to migrate from MongoDB to SQL
cryo is the easiest way to extract blockchain data to parquet, csv, json, or python dataframes
Python Streaming DataFrames for Kafka
Dozer is a real-time data movement tool that leverages CDC from various sources and moves data into various sinks.
An end-to-end GoodReads Data Pipeline for Building Data Lake, Data Warehouse and Analytics Platform.
Hop Orchestration Platform
Apache InLong - a one-stop, full-scenario integration framework for massive data
visual data prep powered by python
High performance Rust stream processing engine seamlessly integrates AI capabilities, providing powerful real-time data processing and intelligent analysis.
omniparser: a native Golang ETL streaming parser and transform library for CSV, JSON, XML, EDI, text, etc.
ETL framework for .NET (Parser / Writer for CSV, Flat, Xml, JSON, Key-Value, Parquet, Yaml, Avro formatted files)
📈 Collect customer event data from your apps. (Note that this project only includes the API collector, not the visualization platform)
Polo travels through your database and creates sample snapshots so you can work with real world data in development.
The simple, stupid batch framework for Java
Conduit streams data between data stores. Kafka Connect replacement. No JVM required.
:lipstick: Durable and asynchronous data imports for consuming data at scale and publishing testable SDKs.
Amazon Redshift Database Loader implemented in AWS Lambda