# PingDartDB - Complete Product Requirements Document (Documentation Structure)

```
PingDartDB/
│
├── README.md
│
├── 01_Vision_and_Goals.md
├── 02_Product_Overview.md
├── 03_System_Architecture.md
├── 04_Core_Concepts.md
├── 05_Unified_Storage_Engine.md
├── 06_File_Format.md
├── 07_Memory_Management.md
├── 08_Query_Engine.md
├── 09_SQL_Compatibility.md
├── 10_Document_API.md
├── 11_Index_Engine.md
├── 12_Transaction_Engine.md
├── 13_WAL_and_Recovery.md
├── 14_Cache_Engine.md
├── 15_Replication.md
├── 16_Cluster_Architecture.md
├── 17_Distributed_Storage.md
├── 18_Load_Balancing.md
├── 19_High_Availability.md
├── 20_Backup_and_Restore.md
├── 21_Security.md
├── 22_Authentication.md
├── 23_Authorization.md
├── 24_Encryption.md
├── 25_Audit_Logs.md
├── 26_AI_Integration.md
├── 27_Vector_Search.md
├── 28_Full_Text_Search.md
├── 29_Graph_Queries.md
├── 30_Geo_Spatial.md
├── 31_Event_Streaming.md
├── 32_Triggers.md
├── 33_Stored_Procedures.md
├── 34_Functions.md
├── 35_API_Server.md
├── 36_HTTP_API.md
├── 37_gRPC_API.md
├── 38_WebSocket_API.md
├── 39_TCP_Binary_Protocol.md
├── 40_NodeJS_SDK.md
├── 41_Python_SDK.md
├── 42_Go_SDK.md
├── 43_Java_SDK.md
├── 44_DotNet_SDK.md
├── 45_Rust_SDK.md
├── 46_CLI.md
├── 47_Admin_Portal.md
├── 48_Web_Studio.md
├── 49_Monitoring.md
├── 50_Metrics.md
├── 51_Logging.md
├── 52_Performance.md
├── 53_Benchmarking.md
├── 54_Deployment.md
├── 55_Docker.md
├── 56_Kubernetes.md
├── 57_Cloud.md
├── 58_On_Premise.md
├── 59_Testing.md
├── 60_Roadmap.md
│
├── api/
│   ├── CRUD.md
│   ├── Query.md
│   ├── Document.md
│   ├── Admin.md
│   ├── Authentication.md
│   └── Cluster.md
│
├── examples/
│   ├── NodeJS.md
│   ├── Rust.md
│   ├── Python.md
│   ├── Go.md
│   └── Java.md
│
├── diagrams/
│   ├── Architecture.md
│   ├── Storage.md
│   ├── Query.md
│   ├── Replication.md
│   ├── Cluster.md
│   └── Network.md
│
└── LICENSE.md
```

## Technology Stack

* Core Engine: Rust
* Async Runtime: Tokio
* Binary Serialization: Bincode
* Memory Mapping: memmap2
* Compression: LZ4 / Zstd
* Hashing: xxHash
* Networking: Hyper + axum + gRPC (tonic)
* API Gateway: Node.js (Fastify)
* Dashboard: Next.js
* Storage (V1): sled embedded Key-Value store
* Storage (V2 Target): Custom PingDart Storage Engine -> Page Manager -> Disk
* Query Engine: Unified Engine (SQL + Document + GraphQL)

## Primary Features

* **Unified Storage Engine**: Seamlessly supports both Relational (Tables/Rows) and Document (Collections/Documents) paradigms on the same physical storage.
* **Document API**: Powerful `POST /document/query` endpoints supporting JSON filtering, projection, limits, and offsets.
* **Automatic & Diverse Indexing**: Primary, Secondary, Composite, Unique, Text, and Vector (Future) indexes.
* **Real-time Subscriptions (Change Streams)**: Push-based real-time document change events via WebSockets (e.g. `.watch()`).
* **Built-in Versioning & Metadata**: Native `_id`, `_version`, `_createdAt`, `_updatedAt`, `_deleted`, `_owner`, `_tenant` fields on documents.
* **Enterprise Transactions**: `BEGIN`, `INSERT`, `UPDATE`, `DELETE`, `COMMIT`, `ROLLBACK`.
* **AI Readiness**: Native roadmap for Vector Embeddings, Semantic Search, AI Indexes, and RAG architectures.
* **SQL Compatibility**: Legacy/traditional SQL connections via driver.
* **Multi-Language Interfaces**: REST API, GraphQL, gRPC, WebSocket.
* Write-Ahead Logging & Snapshots
* Replication & Clustering
* Multi-Tenant Databases & RBAC
* Backup & Restore

## Release Plan & Strategic Roadmap

### 🚀 Version 1.0 (Core Engine & PostgreSQL Parity Foundation)
* **Write Ahead Log (WAL)**: Sequential log with monotonic LSN, group commit with micro-batched `fsync`, and ARIES crash recovery (Analysis, Redo, Undo).
* **Multi-Version Concurrency Control (MVCC)**: Non-blocking reads/writes with tuple version headers (`xmin`, `xmax`, `cid`) and Snapshot Isolation (SI) Read Views.
* **Custom Page Storage Engine**: Buffer pool manager with fixed 8KB slotted pages, frame table, pin/unpin counts, and Clock/2Q page replacement.
* **PostgreSQL Wire Protocol (`pgwire v3`)**: Native TCP server for direct connections from `psql`, DBeaver, DataGrip, Metabase, and standard PostgreSQL drivers.
* **Advanced Join Engine**: In-memory Grace Hash Join and Sort-Merge Join algorithms replacing slow nested loop scans.

### 🏢 Version 2.0 (Distributed Scale & Enterprise Resilience)
* **Distributed Two-Phase Commit (2PC)**: Cross-shard atomic transactions coordinating prepare, commit, and abort across Raft consensus groups.
* **Declarative Table Partitioning**: `PARTITION BY RANGE` and `PARTITION BY HASH` with CBO compile-time partition pruning.
* **Materialized Views**: Pre-aggregated query caches with incremental and transactional refresh mechanics.
* **External Streaming Connectors**: Native CDC connectors streaming write events directly to Apache Kafka, NATS, and Redis Streams.
* **Parallel Query Engine**: Multi-threaded execution pipelines for high-throughput OLAP scans.

### 🌐 Version 3.0 (Cloud-Native AI Hyper-Database)
* **Autonomous Agent Memory Runtime**: `CREATE AGENT`, `STORE MEMORY`, `RECALL MEMORY` with decay and consolidation.
* **Native In-SQL AI Functions**: `SELECT AI_COMPLETE(...)`, `SELECT AI_EMBED(...)`, and `SELECT AI_RERANK(...)`.
* **Time Travel Queries**: `SELECT * FROM table AS OF TIMESTAMP '...'` using MVCC history undo chains.
* **Billion-Scale Vector Quantization**: Scalar Quantization (SQ8), Product Quantization (PQ), and DiskANN disk-backed graphs.
* **Serverless Scale-to-Zero**: Automatic memory suspension and sub-second cold wakeups.

### Detailed Feature Requirements

#### 1. Unified Storage Engine
* **Goal**: Never force developers to choose between SQL and NoSQL.
* **Mechanism**: The same underlying binary storage structures process traditional `CREATE TABLE` and Document-based JSON inserts natively. 

#### 2. Advanced Document Query API
* **Goal**: Allow complex JSON-based querying scaling effectively without constructing SQL strings.
* **Syntax**: A JSON payload defining `collection`, `where` arrays with `field`/`operator`/`value`, `orderBy`, `limit`, and `offset`.

#### 3. AI Support & Vector Embeddings
* **Goal**: Provide Day 1 readiness for LLM integrations.
* **Mechanism**: Dedicated Vector Index types mapped directly in the schema layer, enabling semantic search right next to transactional lookups.

#### 4. Real-Time Subscriptions
* **Goal**: Provide Firebase-like reactivity.
* **Mechanism**: Watch streams over WebSockets that hook directly into the Transaction/Write-Ahead log to push updates globally.

#### 5. Multi-Tenant Architecture & Admin Controls
* **Goal**: Support multiple isolated databases and users within a single deployed instance.
* **Database Isolation**: Users can be granted access to specific databases with granular Role-Based Access Control (RBAC).