DataOps is an automated, process-oriented methodology, used by analytic and data teams, to improve the quality and reduce the cycle time of data analytics. While DataOps began as a set of best practices, it has now matured to become a new and independent approach to data analytics. DataOps applies to the entire data lifecycle from data preparation to reporting, and recognizes the interconnected nature of the data analytics team and information technology operations.

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

• UpdatedApr 10, 2025
• Python

Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.

• UpdatedApr 11, 2025
• Go

Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..

• UpdatedApr 11, 2025
• Rust

Redpanda Console is a developer-friendly UI for managing your Kafka/Redpanda workloads. Console gives you a simple, interactive approach for gaining visibility into your topics, masking data, managing consumer groups, and exploring real-time data with time-travel debugging.

• UpdatedApr 11, 2025
• TypeScript

An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈

• UpdatedJan 10, 2025
• Jupyter Notebook

Scalable and efficient data transformation framework - backwards compatible with dbt.

• UpdatedApr 13, 2025
• Python

The dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features.

• UpdatedApr 10, 2025
• HTML

Kafka Docker for development. Kafka, Zookeeper, Schema Registry, Kafka-Connect, , 20+ connectors

• UpdatedMar 26, 2025
• Shell

Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.

• UpdatedApr 13, 2025
• Python

Cloud Native DataOps & AIOps Platform | 云原生数智运维平台

• UpdatedApr 11, 2024
• Java

Support agile DataOps Based on Flink, DataX and Flink-CDC, Chunjun with Web-UI

• UpdatedApr 13, 2025
• Java

📙 Awesome Data Catalogs and Observability Platforms.

• UpdatedApr 2, 2025

Optimus is an easy-to-use, reliable, and performant workflow orchestrator for data transformation, data modeling, pipelines, and data quality management.

• UpdatedJun 8, 2024
• Go

Tenzir is the data pipeline engine for security teams.

• UpdatedApr 11, 2025
• C++

DataOps for Microsoft Data Platform technologies.https://aka.ms/dataops-repo

• UpdatedApr 10, 2025
• Shell

A list of tools for annotating data, managing annotations, etc.

• UpdatedAug 1, 2024

Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

• UpdatedApr 7, 2025
• Python

Titan Core - Snowflake infrastructure-as-code. Provision environments, automate deploys, CI/CD. Manage RBAC, users, roles, and data access. Declarative Python Resource API. Change Management tool for the Snowflake data warehouse.

• UpdatedMar 13, 2025
• Python

One framework to develop, deploy and operate data workflows with Python and SQL.

• UpdatedApr 7, 2025
• Python

Open data platform based on Kubernetes. Scaleph supports SeaTunnel、Flink and Doris backended by SeaTunnel on Flink engine、Flink Kubernetes Operator and Doris operator.

• UpdatedJan 10, 2025
• Java