8 repositorios
Tools for real-time transformation and analysis of high-frequency data flows.
Distinguishing note: Focuses on data processing rather than general application architecture.
Explore 8 awesome GitHub repositories matching data & databases · Stream Processing. Refine with filters or upvote what's useful.
DuckDB is an in-process analytical database engine designed to run directly within an application process. As a zero-dependency, embedded system, it provides enterprise-grade SQL data processing capabilities without the overhead of managing a dedicated database server. It is built to handle complex analytical and aggregation tasks by storing and retrieving information in columns, allowing for high-performance relational data manipulation. The engine distinguishes itself through a columnar vectorized execution model that maximizes CPU cache efficiency during query operations. It employs adapti
Handles large datasets by streaming query results and processing data incrementally.
InfluxDB is a specialized time series database platform engineered for the high-speed ingestion, compression, and retrieval of timestamped data at scale. It functions as a distributed metrics platform, providing the infrastructure necessary to organize and analyze massive volumes of time-stamped information to identify trends, patterns, and anomalies within complex data streams. The platform distinguishes itself through a functional dataflow engine that utilizes a specialized programming language for complex analytical transformations and automated tasks. This architecture is supported by a p
Includes a dedicated processing engine for analyzing time-stamped information by creating alerts and transformation jobs.
Dragonfly is a high-performance, multi-model in-memory data store designed to serve as a drop-in replacement for existing database infrastructures. By utilizing a multi-threaded, shared-nothing architecture and a fiber-based concurrency model, it maximizes CPU utilization and minimizes latency for read and write operations. The system supports a wide range of data structures, including strings, hashes, lists, sets, sorted sets, and JSON documents, while maintaining full compatibility with standard industry wire protocols and client libraries. What distinguishes Dragonfly is its focus on effic
Provides real-time stream processing capabilities through log-based data structures and consumer group message delivery.
RethinkDB is a distributed, document-oriented database designed to store and manage JSON-formatted data across scalable clusters. It utilizes a custom log-structured storage engine with B-Tree indexing to ensure high-performance disk I/O and data persistence. The system maintains high availability through automatic sharding and replication, employing a primary-replica voting consensus mechanism to handle node failures and ensure consistent cluster operations. A defining characteristic of the platform is its reactive changefeed engine, which allows applications to subscribe to live data update
RethinkDB processes large result sets using cursors to iterate over data lazily, or converts streams into arrays for smaller datasets.
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
Enables real-time analysis and alerting directly on incoming data streams.
This project is a feature-rich Go client library designed for interacting with Redis. It serves as a comprehensive interface for managing remote data stores, enabling developers to execute standard database commands, handle complex data structures, and perform asynchronous operations within Go applications. The library distinguishes itself through its support for advanced Redis capabilities, including connection pooling, pipelining, and transactional integrity. It provides specialized primitives for managing distributed clusters, including automated topology updates and request routing to sha
Provides tools for real-time transformation and analysis of high-frequency data flows.
This project is a comprehensive programming tutorial and technical guide focused on the Java 8 language specification. It provides educational resources for implementing functional programming patterns, utilizing modern language syntax, and adopting updated API standards. The guide covers the transition to functional programming through the use of lambda expressions, method and constructor references, and functional interfaces. It also details the use of default interface methods to extend logic without breaking existing classes and the implementation of repeatable annotations. Additional co
Explains how to process element sequences using filters, maps, and reductions.
This project is a high-performance MQTT broker and IoT data platform designed to manage millions of concurrent device connections. It provides a scalable infrastructure for ingesting, processing, and routing telemetry data across distributed systems, utilizing an actor-based concurrency model to maintain high availability and state synchronization across cluster nodes. The platform distinguishes itself through integrated stream processing and edge computing capabilities. It allows users to execute declarative SQL-based rules directly against incoming message streams for real-time filtering, t
Enables real-time data transformation, filtering, and routing by executing declarative SQL queries against incoming message streams.