Open-source alternatives to Connect

Delta is a lakehouse table format that brings ACID transactions and data warehouse consistency to large scale data lakes on cloud object storage. It serves as an ACID transaction manager, coordinating atomic commits and serializable isolation for concurrent reads and writes across distributed compute engines. The project provides a multi-engine interoperability layer that uses format translation to allow diverse SQL engines and processing frameworks to read and write the same tables. It functions as a data versioning system, utilizing a transaction log to enable time travel, historical snapsh

Debezium is a distributed change data capture platform that streams row-level database modifications as real-time events. By parsing database transaction logs, the system broadcasts structural and data changes to message brokers, enabling reactive processing and data integration across distributed architectures. The platform utilizes log-based capture to extract modifications directly from transaction logs, ensuring minimal impact on source system performance while maintaining the original commit order of operations. It employs database-specific connector adapters to translate proprietary bin

Arroyo is a high-performance stream processing platform built in Rust. It executes continuous SQL queries on streaming data with event-time semantics, enabling accurate windowed aggregations, joins, and stateful computations on unbounded event streams. The platform uses native Rust execution for high throughput and low latency, with periodic checkpointing for exactly-once fault tolerance and horizontal scaling across distributed workers. The system integrates deeply with Kafka for reading and writing topics with exactly-once delivery and supports change data capture (CDC) from MySQL and Postg

Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer

Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis

Uptrace is an OpenTelemetry-based observability platform designed to collect, store, and analyze distributed traces, metrics, and logs. It functions as a centralized logging backend, a distributed tracing system, and a metrics engine to monitor application performance and system health. The platform is distinguished by AI-powered operational capabilities, allowing users to query telemetry data and manage monitoring dashboards using natural language. It specifically includes specialized monitoring for generative AI pipelines, tracking token usage and response quality for LLM interactions and r

Unstructured is an enterprise-grade data orchestration engine designed to transform raw, unstructured files into structured, machine-readable formats. It functions as a comprehensive platform for document ingestion, partitioning, and enrichment, specifically engineered to prepare complex data for retrieval-augmented generation and agentic AI workflows. The platform distinguishes itself through its sophisticated document processing strategies, which combine rule-based extraction with vision-language models to handle diverse file layouts, tables, and images. It provides a modular architecture t

Rudder Server is a customer data platform and event routing pipeline designed to collect, transform, and route customer event data from various sources to data warehouses and business tools. It functions as a customer identity resolver, linking identifiers from multiple sources to build a unified identity graph and comprehensive behavioral customer profiles. The system differentiates itself through reverse ETL capabilities, which push processed customer segments and audiences from data warehouses back into operational third-party applications. It also provides a containerized data plane for K

This project is a streaming data integration framework that captures real-time database changes and synchronizes them with downstream systems. It operates as a distributed streaming ETL and database synchronizer, reading database logs and snapshots to propagate row-level modifications to target sinks. The system supports declarative data integration, allowing users to define source-to-sink data flows using SQL or YAML configurations. It distinguishes itself by automating schema evolution to maintain synchronization when source structures change and ensuring exactly-once delivery and processin

Dinky is a real-time data platform for developing, deploying, and operating streaming applications based on Apache Flink. It functions as a SQL streaming IDE and a real-time data pipeline orchestrator, providing a web-based environment for writing and verifying queries with integrated logic plan visualization and lineage tracking. The platform acts as a distributed cluster manager, allowing the registration, monitoring, and administration of multiple processing clusters from a centralized interface. It also serves as a change data capture integration tool, synchronizing real-time database cha

Sarama is an Apache Kafka Go client library that provides native support for the Kafka protocol. It includes a protocol client for managing offsets and timestamps, a producer implementation for sending messages, and a consumer group coordinator to balance workloads across multiple instances. The library enables high throughput data streaming through concurrent message production and maintains strict partition ordering during network retries. It supports secure communication with Kafka brokers using certificate-based encryption to protect data traffic. The project covers a broad range of dist

Canal is a database replication middleware that performs change data capture by simulating a database replica. It monitors transaction logs to stream incremental data modifications to downstream systems in real time, acting as an event streaming infrastructure that transforms low-level binary logs into structured, consumable message streams. The project distinguishes itself through a high-throughput architecture that utilizes concurrent multi-threaded parsing and stateful log position tracking to ensure reliable data delivery. It employs a pluggable sink architecture that decouples data extra

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

Maxwell is a MySQL change data capture tool and binlog streaming application that converts database modifications into structured JSON events. It functions as a data pipeline that reads MySQL binary logs to synchronize changes across external indices, search engines, and distributed messaging systems such as Kafka. The project provides capabilities to maintain persistent audit trails by recording a chronological history of all database modifications. It enables real-time data synchronization and event-driven architecture integration by streaming database changes to external platforms to trigg

Apache NiFi is a flow-based programming platform that enables the visual design, monitoring, and management of data pipelines. At its core, it provides a web-based visual dataflow designer where users build directed graphs of processors to route, transform, and mediate data movement between any source and destination without writing custom code. The system records fine-grained data provenance for every data item from ingestion to delivery, supporting audit, debugging, and replay of data lineage. The platform distinguishes itself through a zero-master cluster architecture that distributes proc

RisingWave is a cloud-native streaming database and real-time analytics engine that uses standard SQL to process continuous data streams. It functions as a streaming data lakehouse, combining the capabilities of a streaming SQL database with a platform that integrates streaming ingestion with open table formats. The system is distinguished by its use of the PostgreSQL wire protocol, allowing it to integrate with existing SQL tools and drivers. It employs a decoupled compute and storage architecture, persisting streaming state and materialized views in cloud object storage to enable independen

Chunjun is a distributed data integration framework and SQL-based ETL pipeline designed to synchronize data between heterogeneous sources. It functions as a change data capture tool and a heterogeneous data synchronizer, utilizing a distributed processing environment to move and transform data across different database types. The system is distinguished by its plugin-based connector architecture, which allows for the development of custom source and sink plugins to extend connectivity to unsupported data systems. It supports real-time change data capture from relational database logs and impl

This project serves as a comprehensive technical reference for the architecture and design of data-intensive applications. It provides a structured analysis of the fundamental principles required to build reliable, scalable, and maintainable software systems, covering the core trade-offs inherent in modern data infrastructure. The repository explores the mechanics of distributed data management, including strategies for replication, partitioning, and achieving consensus across multiple nodes. It details the design of storage engines, indexing techniques, and transaction management models, whi

DataX is a distributed data integration framework and plugin-based ETL tool designed for synchronizing large datasets between heterogeneous sources and destinations. It functions as a JDBC data migration engine and offline synchronization tool, enabling the movement of data between relational databases, NoSQL stores, and object storage. The system utilizes a plugin-based connector architecture that decouples reader and writer logic, allowing it to map and transform data types across different storage engines using a standardized internal representation. This design supports heterogeneous data

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

FastStream is an asynchronous Python framework designed for building event-driven microservices. It provides a unified abstraction layer for interacting with various message brokers, enabling developers to manage event production and consumption through a consistent interface while maintaining access to native provider-specific features. The framework centers on a decorator-based routing model that binds application logic directly to broker topics, supported by a built-in dependency injection container that resolves resources at runtime. The framework distinguishes itself through its deep int

franz-go is a low-level Go client library and wire protocol implementation for producing, consuming, and administering Kafka clusters. It functions as a zero-allocation network driver that utilizes a direct TCP communication layer to handle requests and responses. The project integrates a schema registry client for encoding and decoding structured data. It provides a programmatic interface for cluster administration, including the management of topics, access control lists, and broker configurations. The library covers data consumption through consumer groups, message production with transac

CAP is a .NET distributed transaction framework and event bus designed to manage asynchronous communication in microservices. It implements the outbox pattern to ensure eventual consistency and reliable message delivery by persisting messages in local database tables until transactions commit. The framework includes a distributed message monitor and web dashboard for tracking the status of sent and received messages. It provides tools for event traffic visualization, distributed request tracing, and the ability to manually trigger retries for failed delivery attempts. The system supports var

Hyperf is a high-performance PHP coroutine framework designed for building microservices and middleware. It utilizes non-blocking coroutines to handle high concurrency and low-latency request processing, providing a foundation for scalable distributed systems. The framework is distinguished by an aspect-oriented programming based dependency injector that enables pluggable components and meta-programming. It includes a coroutine-optimized object-relational mapper with integrated model caching and an orchestration toolkit for microservice governance, featuring service discovery, circuit breaker

TiDB is a horizontally scalable, distributed SQL database designed to provide consistent transactional storage and high-performance analytical processing within a single unified architecture. It utilizes a decoupled compute-storage design and a distributed key-value storage layer to ensure horizontal scalability and efficient range-based queries. By employing a consensus-based replication algorithm, the system maintains high availability and automatic failover across multiple nodes and geographical regions. The platform distinguishes itself through its hybrid transactional and analytical proc

Zellij is a terminal multiplexer and workspace manager designed to organize command-line sessions into persistent, reconfigurable layouts. It functions as a terminal plugin framework, allowing users to extend their environment with modular, event-driven components that interact with the host through a structured message-passing protocol. The project distinguishes itself through a layout-engine-based architecture that decouples visual pane arrangements from process execution, enabling automated and repeatable terminal workflows. It includes integrated support for web-based remote access, facil

Verdaccio is a registry server that implements the npm protocol to store, serve, and manage software dependencies. It functions as a private registry proxy for Node.js packages, allowing organizations to host internal packages while caching public modules. The system features a pluggable middleware architecture that enables the extension of registry behavior through custom plugins for authentication and storage backends. It supports scalable remote data management by offloading package files to S3-compatible object stores. The platform covers package lifecycle management, including publishin