erikgrinaker/toydb

Features

• Distributed SQL Databases - Implements a relational database engine designed to scale horizontally while maintaining transactional consistency.
• Raft Consensus Implementations - Synchronizes a command log across a cluster of nodes using the Raft consensus algorithm for fault tolerance.
• ACID Transactional Cores - Ensures data integrity using snapshot isolation and multi-version concurrency control to prevent dirty and phantom reads.
• Historical Data Querying Interfaces - Allows retrieval of the database state from specific points in the past using logical timestamps.
• Time-Travel Query Interfaces - Enables retrieval of past table states using snapshot identifiers or transaction timestamps.
• Data Joins - Implements general purpose joining functionality to merge columns from multiple tables based on shared keys.
• Data Querying - Provides interfaces for filtering, sorting, and retrieving stored data collections.
• Data Replication - Synchronizes an ordered command log across distributed nodes to ensure data consistency and availability.
• Table Schemas - Supports the creation of tables with specific data types, primary keys, unique constraints, and foreign key relationships.
• SQL Query Execution - Executes structured SQL statements and transactions using an optimized engine to retrieve or modify data.
• Schema Definitions - Provides capabilities to create and remove tables with basic datatypes, primary keys, foreign keys, and column indexes.
• Distributed Consensus Protocols - Replicates state across a cluster using a consensus protocol to maintain consistency across all nodes.
• Consensus Algorithms - Implements consensus algorithms to ensure all nodes in the cluster agree on the sequence of operations.
• Fault Tolerant Storage - Maintains data availability and operational status as long as a majority of cluster nodes remain functional.
• Multi-Version Concurrency Control - Tracks data versions via logical timestamps to provide snapshot isolation and enable time-travel queries.
• Multi-Version Concurrency Controls - Uses multi-version concurrency control to enable lock-free reads and writes via data versioning.
• Multi-Version Concurrency Control - Utilizes multi-version concurrency control to provide snapshot isolation and ensure data integrity during concurrent operations.
• Query Execution Pipelines - Processes SQL statements by pulling and transforming data rows through a pipeline of operator nodes.
• Referential Integrity Constraints - Blocks deletions, updates, or insertions that violate primary key constraints or foreign key references.
• Relational Data Modeling - Provides capabilities for organizing data into structured tables with primary keys and foreign key relationships.
• Row Deletions - Removes rows from a table that match a specific boolean condition.
• Row Insertions - Provides the ability to add new records to tables using standard SQL insert operations.
• SQL-Based Row Updates - Allows modification of existing records in a table using SQL expressions and conditional predicates.
• SQL Query Execution Engines - Provides an engine that processes standard SQL commands while maintaining strict consistency and isolation.
• Strong Consistency Guarantees - Guarantees linearizability by routing writes through a leader and confirming them via a quorum.
• Table Deletion - Permanently deletes a table and all its associated data from the system.
• Log-Structured Storage Engines - Persists data to an append-only file and maintains an in-memory index of keys to file offsets.
• Replicated State Machines - Maintains identical state across all nodes by applying an ordered sequence of transactions.
• Write Conflict Resolution Policies - Detects concurrent transactions modifying the same key and resolves conflicts using specific policies.
• Mathematical Evaluators - Computes results using standard arithmetic operators, floating point math, and three-valued logic.
• Grouped Aggregations - Reduces grouped data into scalar summaries such as average, count, and sum.
• Append-Only Log Stores - Writes data to an append-only log while maintaining an in-memory map of keys to file offsets.
• Pluggable Storage Drivers - Decouples database logic from the persistence layer using a pluggable interface for interchangeable storage engines.
• Pluggable Storage Engines - Supports interchangeable storage backends, including log-structured and in-memory engines.
• Query Planning - Rewrites logical execution plans using heuristic strategies to reduce data transmission and computation.
• SQL Abstract Syntax Tree Parsing - Processes SQL queries into abstract syntax trees to enable programmatic analysis and execution.
• SQL Aggregate Functions - Provides standard SQL aggregate functions for calculating sums, counts, and averages over datasets.
• Storage Backend Adapters - Supports swapping between different data persistence layers such as log-structured stores or in-memory engines.
• SQL Expression Evaluation - Computes results using logical, comparison, mathematical, and string operators including pattern matching with wildcards.
• Storage Abstractions - Uses trait-based interfaces to decouple the core database logic from the underlying persistence layer.
• Database Systems - Distributed SQL database implementation for educational purposes.
• Databases & Data - Distributed SQL database implementation for educational purposes.

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