Projects sharing features with Starrocks

YDB is a distributed SQL database and analytical engine designed for horizontal scalability and strong consistency. It functions as a multi-model system that supports transactional and analytical workloads through a distributed architecture providing serializable ACID transactions. The system is distinguished by its broad protocol compatibility, implementing the PostgreSQL wire protocol for standard SQL drivers and the Kafka protocol for messaging and streaming. It further serves as a vector database, supporting vector indexes and approximate nearest neighbor searches for semantic search and

Doris is a distributed SQL data warehouse designed for high-performance analytical workloads and real-time data processing. It functions as a unified platform that integrates traditional relational warehousing with lakehouse query capabilities, allowing users to execute analytical operations directly against external data lakes without requiring data migration. The system distinguishes itself through a shared-nothing, massively parallel processing architecture that utilizes vectorized query execution and columnar storage to maintain sub-second latency. It supports dynamic schema evolution, en

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

Apache Hive is a SQL-on-Hadoop data warehouse that enables querying and managing petabytes of data stored in distributed storage such as HDFS and cloud storage services. It provides a familiar SQL interface for batch analytics and reporting, supported by a core set of components including the HiveServer2 Thrift service for remote query execution, the Hive Metastore Service for central metadata management, the Hive ACID Transaction Engine for concurrent read-write operations, and the Hive LLAP Interactive Engine for low-latency analytical processing. The WebHCat REST API offers an HTTP interfac

Apache Spark is a unified distributed data processing engine designed for large-scale data analysis and computation graphs. It functions as a distributed machine learning framework, a graph processing system, a real-time stream processor, and a SQL analytics engine. The system enables the execution of distributed SQL querying, large-scale graph analysis, and real-time stream analytics across clusters of machines. It also provides a scalable environment for implementing machine learning algorithms and predictive model development on massive datasets. The engine incorporates relational query e

Calcite is a framework for parsing, optimizing, and translating SQL queries into relational algebra for execution across diverse data sources. It functions as a cross-source query engine, a SQL parsing library, and a relational algebra optimizer. The project provides a cost-based optimization engine that transforms logical query plans into efficient physical execution plans using pluggable rules. It utilizes translation adapters to convert standard SQL requests into the native formats of external databases and messaging systems, enabling data federation across heterogeneous storage systems.

Kylin is a distributed OLAP engine designed for executing fast SQL queries on massive datasets. It utilizes multi-dimensional data cubes to pre-calculate data aggregates, enabling sub-second response times for large-scale analytical queries and big data analytics. The system focuses on large-scale data warehousing and multi-dimensional data modeling. It allows for the organization and querying of vast amounts of structured data to support business intelligence and reporting workflows through distributed SQL querying.

Trino is a distributed SQL query engine designed for large-scale data analytics. It functions as a data federation platform, providing a unified interface that allows users to execute complex analytical queries across multiple heterogeneous data sources simultaneously without requiring data movement or transformation. The engine utilizes a massively parallel processing architecture to scale compute resources across clusters for high-speed data retrieval. It distinguishes itself through a cost-based query optimizer that analyzes metadata to determine efficient execution plans, alongside dynami

ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale data aggregation. It functions as a distributed data warehouse capable of processing petabytes of information, while also providing an embedded engine that integrates directly into applications for native query capabilities without external dependencies. The system is built to handle high-throughput ingestion and complex analytical workloads, delivering millisecond-level latency for interactive dashboards and operational monitoring. The platform distinguishes itself through ad

Daft is a distributed dataframe library and multimodal data processor designed to handle large-scale structured and unstructured data. It functions as a vectorized execution engine that processes tables alongside images, audio, and video, utilizing a unified schema to manage diverse data types. The project distinguishes itself by combining distributed data engineering with large-scale AI inference. It provides an AI data pipeline for batch-optimizing model prompts and generating high-dimensional text embeddings, while utilizing zero-copy memory sharing to execute custom Python functions witho

Databend is a cloud-native data warehouse and OLAP database designed for large-scale analytics. It functions as a SQL-compliant engine and serverless analytics platform that separates compute from storage to allow for independent scaling. The system integrates vector database capabilities, indexing high-dimensional embeddings to enable semantic, hybrid, and full-text searches across massive datasets. It further distinguishes itself through serverless compute management that automatically scales resources based on demand and shuts them down during idle periods. The platform covers a broad set

YugabyteDB is a distributed SQL database and relational data store designed for horizontal scalability and high availability across multiple nodes or regions. It functions as a cloud-native system that ensures continuous availability and supports PostgreSQL compatible query languages and drivers. The system includes specialized capabilities as a vector database for AI, utilizing high-dimensional indexing to perform similarity searches. It is engineered as a multi-region cloud database that synchronizes data across different geographic locations to maintain global availability. The project co

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

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

AliSQL is a fork of MySQL by Alibaba that extends the relational database management system with enhancements for high performance, scalability, and enterprise-grade availability. It retains the core MySQL identity as a SQL-based database for storing, organizing, and retrieving structured data, while adding optimizations for large-scale transactional and analytical workloads. The project differentiates itself through a set of Alibaba-specific improvements, including a columnar engine for accelerating analytical queries directly on MySQL tables, and a distributed, shared-nothing NDB Cluster en

This is a Backend as a Service SDK for Apple platforms, providing a collection of libraries that connect iOS and macOS applications to cloud databases, authentication services, and serverless infrastructure. It serves as a developer kit for integrating real-time data synchronization, file storage, and push notifications into native apps. The SDK is distinguished by its generative AI integration, which routes text and multimodal prompts between on-device models and cloud-hosted large language models. It further differentiates itself with a specialized app distribution tool for managing pre-rel

This project is a curated collection of academic papers, books, and technical resources designed for studying the architecture and implementation of database management systems. It serves as a comprehensive educational guide for engineers and researchers looking to understand the fundamental principles behind modern data storage and retrieval. The repository distinguishes itself by providing structured learning paths across critical database domains, including the design of persistent storage engines, the mechanics of query optimization, and the complexities of distributed transaction managem

FoundationDB is an ACID-compliant distributed transactional key-value store. It functions as a scalable database engine that ensures strict serializability and data consistency across a cluster of servers using a shared-nothing architecture. The system is distinguished by its multi-region replication capabilities, allowing data to be synchronized across different datacenters for high availability and disaster recovery. It utilizes optimistic concurrency control to manage distributed transactions and employs a majority-based coordination system to maintain cluster state. The platform provides

QuestDB is a high-performance, distributed time-series database designed for the ingestion, storage, and analysis of massive datasets. It functions as a real-time analytics platform that utilizes a columnar storage engine to optimize disk input and output, enabling efficient analytical scans and complex windowing operations on streaming data. The platform distinguishes itself through specialized capabilities for handling asynchronous time-series streams, including advanced join algorithms that align disparate data sets based on precise timestamp lookups. It supports high-volume ingestion thro

This project is a reactive, offline-first NoSQL database engine designed for JavaScript applications. It provides a robust framework for managing application state by synchronizing data across browsers, mobile devices, and server-side runtimes. By treating local storage as the primary source of truth, it enables applications to remain functional without network connectivity, automatically reconciling changes with remote backends once a connection is restored. The database distinguishes itself through a modular architecture that supports cross-environment synchronization and high-performance d

FalkorDB is a high-performance graph database management system and vector graph database. It serves as a knowledge graph construction tool and a GraphRAG knowledge store, integrating structured property graphs with vector search to provide grounded context for large language models. The engine is designed as a multi-tenant graph engine, capable of hosting thousands of isolated datasets within a single instance. The system distinguishes itself by using linear algebra for query execution, treating relationship tensors as matrix multiplications to achieve low-latency multi-hop traversals. It ut

Redis is a high-performance in-memory key-value store that functions as a distributed cache, message broker, and NoSQL database. It provides sub-millisecond read and write access to data stored in RAM and can operate as a vector database for indexing high-dimensional embeddings. The system supports a wide range of data storage and synchronization primitives, including the management of strings, hashes, lists, sets, and JSON documents. It enables real-time data operations through atomic transactions, hybrid persistence using snapshots and append-only logs, and high-availability configurations

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

Noria is a dynamic dataflow engine and materialized view database that transforms expensive read operations into fast keyed lookups. It operates as a stateful system that incrementally updates dependent views as underlying relational base tables change. The system can function as a MySQL protocol emulator, mimicking the binary protocol to allow applications to fetch precomputed data without changing client code. It can also be used as a Rust embedded database, integrating the server directly into a program via native bindings to perform dataflow operations without external coordination. The

LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters

Cube is a semantic data layer that provides a unified framework for defining business metrics, dimensions, and relationships across diverse data sources. By acting as a headless business intelligence engine, it transforms raw data into a governed model that can be queried via SQL, REST, and GraphQL interfaces. This architecture ensures consistent data definitions and logic across all downstream analytical applications and reporting tools. The platform distinguishes itself through its integrated conversational AI capabilities, which allow users to explore data using natural language. It orches

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