Temporal database views

TDengine is a distributed time-series database designed for the high-speed ingestion, compression, and retrieval of timestamped metrics and sensor data. It functions as a SQL-compatible analytics engine, allowing users to perform complex operations on massive volumes of time-ordered information using standard relational syntax. The platform is built to serve as a backend foundation for industrial IoT environments, managing real-time data streams and device metadata through a cluster-based architecture. The system distinguishes itself through a distributed sharding architecture that uses consi

An immutable SQL database for application development, time-travel reporting and data compliance. Developed by @juxt

Temporal Tables is a PostgreSQL database extension and trigger function library that implements system-versioned tables and database history tracking. It automates the maintenance of historical data archives by intercepting write operations to capture previous row versions when updates and deletions occur. The extension manages record lifespans through transaction-time interval mapping, using paired timestamp columns to track active validity periods and relational schema linking to connect primary tables to their corresponding history archives. It includes concurrent conflict resolution mech

Databus is a distributed change data capture system and database transaction log streamer. It extracts data modifications from source logs and streams them to downstream consumers to keep secondary data stores and caches consistent. The system functions as a source-agnostic data pipeline and distributed event relay. It uses a network of processes to decouple database sources from consumers, routing change streams across a network to multiple targets regardless of the original source system. The project covers real-time data synchronization and distributed pipeline monitoring. This includes t

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

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

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

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

InfluxDB is a high-performance time-series database designed for collecting, storing, and querying time-stamped metrics and event data. It functions as a columnar time-series store and a real-time analytics engine, providing a network-accessible interface for retrieving and analyzing temporal records. The system utilizes a specialized columnar storage format to support high ingestion rates and efficient data retrieval. It incorporates a programmable runtime for executing custom plugins and triggers, including integration for processing and transforming incoming data streams. The platform cov

Audited is a Ruby on Rails audit log library and change data capture framework. It tracks model changes by recording previous and current attribute values during create, update, and destroy operations to maintain a complete history of database modifications. The system functions as a database versioning tool and user activity tracker. It allows for the retrieval of historical record states by timestamp or index, enables reverting models to previous versions, and associates record modifications with specific user identities and remote IP addresses. The library includes capabilities for sensit

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