One framework to develop, deploy and operate data workflows with Python and SQL.
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Updated
May 30, 2024 - Python
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.
One framework to develop, deploy and operate data workflows with Python and SQL.
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, with more integrations coming..
Open source security data pipelines.
Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
Efficient data transformation and modeling framework that is backwards compatible with dbt.
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. 📈
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.
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.
Meteor is an easy-to-use, plugin-driven metadata collection framework to extract data from different sources and sink to any data catalog.
Open data platform based on Kubernetes. Scaleph supports SeaTunnel、Flink and Doris backended by SeaTunnel on Flink engine、Flink Kubernetes Operator and Doris operator.
Frontier is an all-in-one user management platform that provides identity, access and billing management to help organizations secure their systems and data. (Open source alternative to Clerk)
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.
DataOps TestGen is part of DataKitchen's Open Source Data Observability. DataOps TestGen delivers simple, fast data quality test generation and execution by data profiling, new dataset screening and hygiene review, algorithmic generation of data quality validation tests, ongoing testing of new data refreshes, & continuous data anomaly monitoring
Installer for DataKitchen's Open Source Data Observability Products. Data breaks. Servers break. Your toolchain breaks. Ensure your team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end to end.
DataOps Observability is part of DataKitchen's Open Source Data Observability. DataOps Observability monitors every data journey from data source to customer value, from any team development environment into production, across every tool, team, environment, and customer so that problems are detected, localized, and understood immediately.
An open source development framework to help you build data workflows and modern data architecture on AWS.
Polyaxon Core Client & CLI to streamline MLOps
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
An Git-like version control file system for data lineage & data collaboration.