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Meltano is an open-source platform for building, running, and orchestrating ELT (Extract, Load, Transform) data pipelines. It provides a declarative, YAML-driven configuration system that defines entire pipeline workflows, including data connectors, schedules, and transformations, without requiring imperative code. The platform is built on the Singer specification for data connectors and integrates with dbt for SQL-based transformations and Apache Airflow for scheduling and…
The main features of meltano/meltano are: Business Intelligence, Data Integration, Data Pipelines and Orchestration.
Projects with overlapping indexed features include: airbytehq/airbyte — Airbyte is a data integration platform designed to synchronize information between diverse applications, databases,… singer-io/getting-started — Singer is an open source standard for moving data between databases, web APIs, files, queues, and just about anything… jitsucom/jitsu — Jitsu is an open-source customer data platform designed to orchestrate event data pipelines. It captures, transforms,… astronomer/dag-factory — Dag-factory is a framework for constructing and managing Apache Airflow data pipelines through declarative… apache/superset — Superset is a web-based business intelligence platform designed for data exploration, visualization, and interactive… apache/inlong — Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file…
Singer is an open source standard for moving data between databases, web APIs, files, queues, and just about anything else you can think of. The Singer spec describes how data extraction scripts — called “Taps” — and data loading scripts — called “Targets” — should communicate using a standard…
Airbyte is a data integration platform designed to synchronize information between diverse applications, databases, and data warehouses. It functions as an extract, transform, and load orchestrator that manages automated data movement workflows across cloud, on-premise, and hybrid environments. The platform provides a standardized interface for connectors, enabling the movement of structured and unstructured data while maintaining stateful checkpoints for reliable incremental syncing. The platform distinguishes itself through a containerized architecture that isolates connectors to prevent de
Jitsu is an open-source customer data platform designed to orchestrate event data pipelines. It captures, transforms, and routes behavioral data from web and server sources into data warehouses and analytics tools, providing a unified infrastructure for managing event streams. The platform distinguishes itself through its focus on self-hosted, containerized operations that grant users full control over their data security and privacy. It features a robust identity resolution engine that stitches disparate user identifiers into persistent profiles across sessions and devices, alongside program
Dag-factory is a framework for constructing and managing Apache Airflow data pipelines through declarative configuration files. By replacing manual procedural code with structured YAML definitions, it enables the programmatic generation of complex workflow structures, task dependencies, and execution schedules. The project distinguishes itself by mapping configuration keys directly to Python class constructors and operators, allowing for the dynamic instantiation of objects and custom logic. It supports hierarchical configuration inheritance to standardize settings across environments and pro