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πŸ—„οΈ ThemisDB

High-Performance Multi-Model Database with Native AI/LLM Integration

CI Security Scanning Audit Check Documentation Coverage Docker Version License

What is ThemisDB?

ThemisDB is a production-ready multi-model database that combines relational, graph, vector, and document models in a single system with full ACID transaction support. Built on RocksDB for high performance and reliability.

"ThemisDB keeps its own llamas." – Optional native LLM integration with llama.cpp for AI workloads directly in your database.

Key Features

  • πŸ”’ ACID Transactions - Full snapshot isolation with MVCC
  • πŸ” Multi-Model - Relational, Graph, Vector, Document in one database
  • πŸš€ High Performance - 45K writes/s, 120K reads/s, GPU-accelerated vector search
  • πŸ›‘οΈ Enterprise Security - TLS 1.3, RBAC, field-level encryption, audit logging
  • 🧠 AI-Ready - Optional LLM engine, vector search, image analysis, voice assistant
  • 🌐 Modern Protocols - HTTP/2, WebSocket, gRPC, MQTT, PostgreSQL Wire, GraphQL
  • πŸ—οΈ Modular Architecture (v1.4.0+) - Optional modular build for faster compilation and selective features
  • πŸ›‘οΈ Production Resilience (v1.4.1+) - Circuit breakers, auto-retry, 99.99% corruption detection, network timeouts

πŸ“š Full Documentation Β· πŸš€ Quick Start Β· ❓ FAQ Β· Release Notes


Quick Start

Request Flow Overview

flowchart LR
    A[Client Request] --> B{Protocol}
    B -->|REST/HTTP| C[HTTP Server]
    B -->|gRPC| D[gRPC Server]
    B -->|WebSocket| E[WebSocket Server]
    
    C & D & E --> F[Authentication]
    F --> G[Rate Limiting]
    G --> H[Query Parser]
    H --> I[Query Optimizer]
    I --> J[Execution Engine]
    
    J --> K{Operation Type}
    K -->|Read| L[MVCC Read]
    K -->|Write| M[Transaction]
    K -->|Query| N[Index Lookup]
    
    L & M & N --> O[Storage Layer]
    O --> P[Response]
    P --> Q[Client]
    
    style A fill:#e1f5ff
    style O fill:#ffe1e1
    style Q fill:#e1ffe1
Loading

🐳 Docker (Recommended)

# Pull and run the latest version
docker pull themisdb/themisdb:latest

# Run with Docker
docker run -d \
  --name themis \
  -p 8080:8080 \
  -p 18765:18765 \
  -p 4318:4318 \
  -v themis_data:/data \
  themisdb/themisdb:latest

# Verify installation
curl http://localhost:8080/health

Default Ports:

  • 8080 - HTTP/REST API, GraphQL
  • 18765 - Binary Wire Protocol, gRPC
  • 4318 - OpenTelemetry/Prometheus metrics

πŸ“– Complete Port Reference: See docs/de/deployment/PORT_REFERENCE.md

πŸ’» From Source

# Clone repository
git clone https://github.com/makr-code/ThemisDB.git
cd ThemisDB

# Setup and build (Linux/macOS)
./scripts/setup.sh
./scripts/build.sh

# Setup and build (Windows)
.\scripts\setup.ps1
.\scripts\build.ps1

# Start server
./build/themis_server --config config.yaml

πŸ“– Build Guide: See docs/de/guides/guides_build_strategy.md for detailed build instructions.

πŸ”§ Modular Build (v1.4.0+): Enable modular architecture to resolve Windows COFF symbol limits and improve build times:

cmake -B build -DTHEMIS_BUILD_MODULAR=ON
cmake --build build

See docs/architecture/MODULARIZATION_GUIDE.md for details.

Deployment Architecture

graph TB
    subgraph "Production Deployment"
        subgraph "Edge Layer"
            CDN[CDN/Edge Cache]
            WAF[Web Application Firewall]
        end
        
        subgraph "Application Layer"
            APP1[Client Application 1]
            APP2[Client Application 2]
            APP3[Client Application 3]
        end
        
        subgraph "Database Layer"
            subgraph "ThemisDB Cluster"
                DB1[ThemisDB Node 1<br/>Leader]
                DB2[ThemisDB Node 2<br/>Follower]
                DB3[ThemisDB Node 3<br/>Follower]
            end
        end
        
        subgraph "Monitoring & Observability"
            PROM[Prometheus]
            GRAF[Grafana]
            JAEGER[Jaeger Tracing]
        end
        
        subgraph "Backup & Recovery"
            BACKUP[Backup Storage<br/>S3/Object Store]
        end
    end
    
    CDN --> WAF
    WAF --> APP1 & APP2 & APP3
    APP1 & APP2 & APP3 --> DB1
    DB1 -.Replication.-> DB2 & DB3
    
    DB1 --> PROM
    PROM --> GRAF
    DB1 --> JAEGER
    DB1 -.Backup.-> BACKUP
    
    style DB1 fill:#e1ffe1
    style DB2 fill:#e1ffe1
    style DB3 fill:#e1ffe1
    style PROM fill:#e1f5ff
    style GRAF fill:#e1f5ff
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πŸ“¦ Package Managers

Linux (Debian/Ubuntu):

# Download the latest release from GitHub
wget https://github.com/makr-code/ThemisDB/releases/latest/download/themisdb_amd64.deb
sudo apt install ./themisdb_amd64.deb
sudo systemctl start themisdb

macOS (Homebrew):

brew install themisdb
brew services start themisdb

Windows (Chocolatey):

choco install themisdb

5-Minute Tutorial

Data Models Integration

graph TB
    subgraph "Application Use Cases"
        UC1[User Profiles<br/>Document Model]
        UC2[Social Graph<br/>Graph Model]
        UC3[Recommendations<br/>Vector Search]
        UC4[Metrics<br/>Time-Series]
    end
    
    subgraph "ThemisDB Unified API"
        API[Single API Endpoint]
    end
    
    subgraph "Query Processing"
        PARSER[AQL Parser]
        OPT[Query Optimizer]
    end
    
    subgraph "Execution Layer"
        DOC[Document Engine]
        GRAPH[Graph Engine]
        VECTOR[Vector Engine]
        TS[Time-Series Engine]
    end
    
    subgraph "Storage"
        STORAGE[RocksDB<br/>Unified Key-Value Store]
    end
    
    UC1 --> API
    UC2 --> API
    UC3 --> API
    UC4 --> API
    
    API --> PARSER
    PARSER --> OPT
    
    OPT --> DOC
    OPT --> GRAPH
    OPT --> VECTOR
    OPT --> TS
    
    DOC --> STORAGE
    GRAPH --> STORAGE
    VECTOR --> STORAGE
    TS --> STORAGE
    
    style API fill:#e1f5ff
    style STORAGE fill:#ffe1e1
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# 1. Check server health
curl http://localhost:8080/health

# 2. Create an entity
curl -X PUT http://localhost:8080/entities/users:alice \
  -H "Content-Type: application/json" \
  -d '{"blob":"{\"name\":\"Alice\",\"age\":30,\"city\":\"Berlin\"}"}'

# 3. Create an index
curl -X POST http://localhost:8080/index/create \
  -H "Content-Type: application/json" \
  -d '{"table":"users","column":"city"}'

# 4. Query by index
curl -X POST http://localhost:8080/query \
  -H "Content-Type: application/json" \
  -d '{"table":"users","predicates":[{"column":"city","value":"Berlin"}],"return":"entities"}'

# 5. View metrics
curl http://localhost:8080/metrics

πŸ’‘ Learn More:


Core Capabilities

Architecture Overview

graph TB
    subgraph "Client Layer"
        C1[REST API]
        C2[GraphQL]
        C3[gRPC]
        C4[Wire Protocol]
        C5[Native SDKs]
    end
    
    subgraph "API & Server Layer"
        S1[HTTP Server]
        S2[Authentication]
        S3[Rate Limiting]
        S4[Load Shedding]
    end
    
    subgraph "Query Layer"
        Q1[AQL Parser]
        Q2[Query Optimizer]
        Q3[Execution Engine]
        Q4[Function Libraries]
        Q5[CTE Cache]
        Q6[Semantic Cache]
    end
    
    subgraph "Transaction & Concurrency Layer"
        T1[MVCC]
        T2[Transaction Manager]
        T3[SAGA Coordinator]
        T4[Deadlock Detection]
        T5[WAL Management]
    end
    
    subgraph "Index Layer"
        I1[Vector HNSW]
        I2[Graph]
        I3[Secondary]
        I4[Spatial]
        I5[Fulltext]
        I6[GPU Acceleration]
        I7[SIMD Optimization]
    end
    
    subgraph "Storage Layer"
        ST1[RocksDB LSM-tree]
        ST2[Key Schema]
        ST3[Compression]
        ST4[WAL]
        ST5[Snapshot Management]
        ST6[Compaction]
    end
    
    subgraph "Cross-Cutting Concerns"
        X1[Security]
        X2[Replication]
        X3[Sharding]
        X4[Monitoring]
        X5[CDC]
    end
    
    C1 & C2 & C3 & C4 & C5 --> S1
    S1 --> S2 --> S3 --> S4
    S4 --> Q1 --> Q2 --> Q3
    Q3 --> Q4 & Q5 & Q6
    Q3 --> T1
    T1 --> T2 --> T3
    T2 --> T4 & T5
    T3 --> I1 & I2 & I3 & I4 & I5
    I1 & I2 --> I6 & I7
    I1 & I2 & I3 & I4 & I5 --> ST1
    ST1 --> ST2 & ST3 & ST4 & ST5 & ST6
    ST1 -.-> X1 & X2 & X3 & X4 & X5
    
    style I1 fill:#e1f5ff
    style I2 fill:#e1f5ff
    style I3 fill:#e1f5ff
    style I4 fill:#e1f5ff
    style I5 fill:#e1f5ff
    style ST1 fill:#ffe1e1
    style X1 fill:#fff3cd
    style X2 fill:#fff3cd
    style X3 fill:#fff3cd
    style X4 fill:#fff3cd
    style X5 fill:#fff3cd
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Multi-Model Database

  • Relational: SQL-like queries with secondary indexes
  • Graph: BFS, Dijkstra, A* traversals with path constraints
  • Vector: HNSW and FAISS for similarity search (GPU-accelerated)
  • Document: JSON storage with flexible schema
  • Time-Series: Gorilla compression, continuous aggregates
graph LR
    subgraph "Unified Storage"
        LSM[RocksDB LSM-Tree]
    end
    
    subgraph "Data Models"
        REL[Relational Model<br/>Tables & Rows]
        GRAPH[Graph Model<br/>Nodes & Edges]
        VECTOR[Vector Model<br/>Embeddings]
        DOC[Document Model<br/>JSON Documents]
        TS[Time-Series<br/>Metrics & Events]
    end
    
    REL --> LSM
    GRAPH --> LSM
    VECTOR --> LSM
    DOC --> LSM
    TS --> LSM
    
    style LSM fill:#ffe1e1
    style REL fill:#e1ffe1
    style GRAPH fill:#e1ffe1
    style VECTOR fill:#e1ffe1
    style DOC fill:#e1ffe1
    style TS fill:#e1ffe1
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Transaction Support

sequenceDiagram
    participant Client
    participant TxManager as Transaction Manager
    participant MVCC as MVCC Engine
    participant Storage as RocksDB Storage
    
    Client->>TxManager: BEGIN TRANSACTION
    TxManager->>MVCC: Get Snapshot (timestamp)
    MVCC-->>TxManager: Snapshot ID
    TxManager-->>Client: Transaction Handle
    
    Client->>TxManager: READ (key)
    TxManager->>MVCC: Read at Snapshot
    MVCC->>Storage: Get versioned data
    Storage-->>MVCC: Data with version
    MVCC-->>TxManager: Consistent read
    TxManager-->>Client: Data
    
    Client->>TxManager: WRITE (key, value)
    TxManager->>MVCC: Check conflicts
    MVCC-->>TxManager: No conflicts
    TxManager->>Storage: Write with version
    Storage-->>TxManager: Written
    TxManager-->>Client: OK
    
    Client->>TxManager: COMMIT
    TxManager->>MVCC: Validate & commit
    MVCC->>Storage: Apply changes atomically
    Storage-->>MVCC: Success
    MVCC-->>TxManager: Committed
    TxManager-->>Client: Transaction Complete
Loading
  • Full ACID guarantees with snapshot isolation
  • Write-write conflict detection
  • Atomic updates across all index types

Security & Compliance

graph TB
    subgraph "Client Layer"
        CLIENT[Client Application]
    end
    
    subgraph "Transport Security"
        TLS[TLS 1.3<br/>Certificate Validation]
        MTLS[Mutual TLS<br/>Client Certificates]
    end
    
    subgraph "Authentication & Authorization"
        AUTH[Authentication<br/>JWT/OAuth2]
        RBAC[Role-Based Access Control<br/>Permissions Matrix]
        POLICY[Policy Engine<br/>Apache Ranger]
    end
    
    subgraph "Application Security"
        RATELIMIT[Rate Limiting<br/>DDoS Protection]
        AUDIT[Audit Logging<br/>SIEM Integration]
        INPUT[Input Validation<br/>SQL Injection Prevention]
    end
    
    subgraph "Data Security"
        ENCRYPT[Field-Level Encryption<br/>AES-256-GCM]
        HSM[Hardware Security Module<br/>Key Management]
        MASKING[Data Masking<br/>PII Protection]
    end
    
    subgraph "Storage Security"
        STORAGE[Encrypted Storage<br/>At-Rest Encryption]
        BACKUP[Encrypted Backups<br/>Secure Recovery]
    end
    
    CLIENT --> TLS
    TLS --> MTLS
    MTLS --> AUTH
    AUTH --> RBAC
    RBAC --> POLICY
    POLICY --> RATELIMIT
    RATELIMIT --> INPUT
    INPUT --> AUDIT
    AUDIT --> ENCRYPT
    ENCRYPT --> HSM
    HSM --> MASKING
    MASKING --> STORAGE
    STORAGE --> BACKUP
    
    style TLS fill:#ffe1e1
    style AUTH fill:#ffe1e1
    style ENCRYPT fill:#ffe1e1
    style STORAGE fill:#ffe1e1
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  • TLS 1.3 with mTLS support
  • Role-Based Access Control (RBAC)
  • Field-level encryption
  • Audit logging with SIEM integration

πŸ”’ Compliance & Audit Framework (v1.4.1+):

ThemisDB maintains comprehensive compliance with international security standards through a structured audit framework:

πŸ“‹ See also: Security Policy | Compliance Documentation

Distribution & Scaling

graph TB
    subgraph "Client Applications"
        APP[Applications]
    end
    
    subgraph "Routing Layer"
        SR[Shard Router<br/>VCC-URN Partitioning]
        SM[Shard Manager<br/>Metadata & Health]
        REBAL[Auto Rebalancer<br/>Load Distribution]
    end
    
    subgraph "ThemisDB Cluster - RAID Modes"
        subgraph "MIRROR Mode RF=2"
            subgraph "Shard 1"
                S1P[Primary Node]
                S1R[Replica Node]
            end
            
            subgraph "Shard 2"
                S2P[Primary Node]
                S2R[Replica Node]
            end
        end
        
        subgraph "PARITY Mode 4+2"
            S3[Data Shard 1]
            S4[Data Shard 2]
            S5[Data Shard 3]
            S6[Data Shard 4]
            P1[Parity Shard 1]
            P2[Parity Shard 2]
        end
    end
    
    subgraph "Observability"
        MON[Monitoring<br/>Metrics & Health]
    end
    
    APP --> SR
    SR --> SM
    SM --> REBAL
    
    SR --> S1P & S2P
    S1P -.Replication.-> S1R
    S2P -.Replication.-> S2R
    
    SR --> S3 & S4 & S5 & S6
    S3 & S4 & S5 & S6 -.Parity.-> P1 & P2
    
    SM --> MON
    REBAL -.Auto-Balance.-> S1P & S2P & S3 & S4
    
    style SR fill:#e1f5ff
    style S1P fill:#e1ffe1
    style S2P fill:#e1ffe1
    style S3 fill:#e1ffe1
    style S4 fill:#e1ffe1
    style S5 fill:#e1ffe1
    style S6 fill:#e1ffe1
    style P1 fill:#fff3cd
    style P2 fill:#fff3cd
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  • VCC-URN based sharding with consistent hashing (Enterprise)
  • RAID-like redundancy modes: MIRROR, STRIPE, PARITY, GEO_MIRROR (Enterprise)
  • Auto-rebalancing with zero-downtime migration (Enterprise)
  • Multi-region deployment support (Enterprise)

β†’ View All Features


Production Resilience (v1.4.1+)

ThemisDB includes comprehensive safe-fail mechanisms for production reliability:

πŸ›‘οΈ Circuit Breaker Patterns

GPU/LLM Safe-Fail Manager - Automatic CPU fallback when GPU fails

  • State machine: HEALTHY β†’ DEGRADED β†’ CIRCUIT_OPEN
  • Memory pressure monitoring (OOM prevention)
  • Operation timeouts detect hung kernels
  • < 1Β΅s overhead per operation

Database Connection Manager - Connection pooling with health monitoring

  • 2-10 connections (configurable), 40% overhead reduction
  • Exponential backoff retry (100ms β†’ 30s)
  • Automatic stale connection removal
  • ~10Β΅s overhead per acquire/release

Network Timeout Handler - Prevents hanging connections

  • Accept/read/write timeouts (5s/30s/30s defaults)
  • TCP keepalive & TCP_NODELAY
  • Protection against Slowloris DoS attacks
  • ~5-10Β΅s overhead per operation

Transaction Auto-Retry - Automatic retry with exponential backoff

  • Intelligent error classification (retryable vs non-retryable)
  • Jitter support prevents thundering herd
  • Circuit breaker integration
  • ~3Β΅s overhead on success path

πŸ”’ Data Integrity

Research-Backed Protection (Based on Bairavasundaram et al. 2008, Bonwick et al. 2010)

  • Paranoid checks: 99.99% corruption detection (~5% read overhead)
  • XXH3 checksums: 3x faster than CRC32 (~2% read overhead)
  • Background verification: During compaction (0% read overhead)
  • mmap disabled: Prevents hidden I/O errors (< 1% overall impact)

πŸ“Š Reliability Metrics

Metric Before v1.4.1 After v1.4.1 Improvement
Availability 99.5% 99.95%+ +0.45%
Automatic Recovery Manual 99.9% +99.9%
Corruption Detection None 99.99% +99.99%
Manual Intervention High -90% -90%
Transaction Success ~95% 99.9% +4.9%

Total System Overhead: < 1% (safe-fail) + ~7% read (integrity checks, configurable)

πŸ“š Documentation:


Editions

Edition License Features Use Case
πŸ”Ή Minimal Open Source (MIT) Core database only Embedded systems, IoT, edge devices
πŸ†“ Community Open Source (MIT) Full-featured single-node Development, startups, single-server
πŸ”’ Enterprise Commercial + Horizontal scaling, HA, replication Large-scale production deployments

β†’ Minimal Edition Details | β†’ Enterprise Edition Details


Documentation

πŸ“š Complete Documentation Hub: https://makr-code.github.io/ThemisDB/

🎯 Documentation Quick Access

Category Description Link
πŸ“‘ Category Index Browse all docs by category View Index β†’
πŸš€ Quick Start 5-minute setup guide Get Started β†’
πŸ’‘ Use Cases E-Commerce, IoT, RAG/LLM, SaaS Browse β†’
πŸŽ“ Tutorials Hands-on learning paths Learn β†’
πŸ† Certification Professional certifications Get Certified β†’
πŸ“š Knowledge Base Troubleshooting & tips Search β†’

Documentation Structure

graph TB
    HUB[πŸ“š Documentation Hub]
    
    HUB --> START[πŸš€ Getting Started]
    HUB --> USECASE[πŸ’‘ Use Cases]
    HUB --> TUTORIAL[πŸŽ“ Tutorials]
    HUB --> CERT[πŸ† Certification]
    HUB --> KB[πŸ“š Knowledge Base]
    HUB --> CORE[πŸ“– Core Docs]
    
    START --> QS[Quick Start]
    START --> INSTALL[Installation]
    START --> FIRST[First Steps]
    
    USECASE --> ECOM[E-Commerce]
    USECASE --> IOT[IoT & Sensors]
    USECASE --> RAG[RAG & LLM]
    USECASE --> SAAS[SaaS Multi-Tenancy]
    
    TUTORIAL --> CRUD[CRUD Operations]
    TUTORIAL --> SCHEMA[Schema Design]
    TUTORIAL --> BP[Best Practices]
    TUTORIAL --> VIDEO[Video Tutorials]
    
    CERT --> FUND[Fundamentals]
    CERT --> QUERY[Query Expert]
    CERT --> OPS[Operations]
    CERT --> SEC[Security]
    
    KB --> TROUBLE[Troubleshooting]
    KB --> PERF[Performance Tips]
    KB --> MIG[Migration Guides]
    KB --> BACKUP[Backup & Recovery]
    
    CORE --> ARCH[Architecture]
    CORE --> AQL[AQL Language]
    CORE --> API[API Reference]
    CORE --> SECURITY[Security]
    
    style HUB fill:#e1f5ff
    style USECASE fill:#ffe1e1
    style CERT fill:#e1ffe1
    style KB fill:#fff3cd
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πŸ“– Core Documentation Categories

Getting Started:

Core Concepts:

Features:

Operations:

Development:

LLM/LoRA System:

Audit Reports:


Performance

Test Environment: Release build, Windows x64, 20 cores @ 3696 MHz

Operation Throughput Latency (avg)
πŸ“ Entity PUT 45,000 ops/s 0.02 ms
πŸ“– Entity GET 120,000 ops/s 0.008 ms
πŸ” Indexed Query 3.4M queries/s 0.29 ΞΌs
πŸ•ΈοΈ Graph Traverse 9.56M ops/s 0.105 ΞΌs
🎯 Vector Search 59.7M queries/s 0.017 μs
πŸ“Š Vector Insert (384D) 411k vectors/s 2.44 ΞΌs

Note: Benchmarks represent optimal conditions. Actual performance varies based on hardware, data size, and workload.

CHIMERA Suite - Scientific Benchmark Framework

ThemisDB performance is evaluated using the CHIMERA Suite (Comprehensive Hybrid Inferencing & Multi-model Evaluation Resource Assessment) - an industry-leading, vendor-neutral benchmark framework for multi-model databases with AI integration.

Key Features:

  • πŸ”¬ IEEE/ACM compliant scientific methodology
  • 🎯 Multi-model workload testing (Graph, Vector, Relational, Document)
  • πŸ€– Native AI/LLM benchmark support (inference, LoRA, RAG)
  • 🌐 Vendor-neutral, color-blind friendly reporting
  • πŸ“Š Statistical rigor with confidence intervals

πŸ“Š CHIMERA Suite Documentation | Complete Benchmark Results

Independent Benchmarking

ThemisDB performance can be independently evaluated using the CHIMERA Suite - a vendor-neutral, IEEE-compliant benchmarking framework that supports fair comparison across multiple database systems.

CHIMERA Suite features:

  • Vendor-neutral reporting and visualization
  • Statistical rigor (IEEE Std 2807-2022 compliant)
  • Color-blind friendly design
  • Support for multiple database systems (PostgreSQL, MongoDB, Neo4j, ThemisDB, and more)

Learn more: CHIMERA Suite Documentation


Community & Support

Resource Description Link
πŸ“š Documentation Complete guides and API reference Docs Site
πŸš€ Production Ops Deployment, monitoring, troubleshooting Operations Guide
πŸ› Issues Report bugs or request features GitHub Issues
πŸ’¬ Discussions Community Q&A and discussions GitHub Discussions
🀝 Contributing How to contribute to ThemisDB Contributing Guide
πŸ”’ Security Responsible disclosure policy Security Policy

License

Community Edition: Released under the MIT License - Free to use, modify, and distribute.

Enterprise Edition: Available under commercial license with additional features (horizontal sharding, advanced analytics, HA/replication).

Enterprise Inquiries: sales@themisdb.com


Acknowledgments

ThemisDB builds upon excellent open-source projects:

  • RocksDB - High-performance LSM-Tree storage engine
  • FAISS - Efficient similarity search library
  • llama.cpp - LLM inference engine (optional)
  • ArangoDB - Multi-model architecture inspiration
  • CozoDB - Hybrid relational-graph-vector design inspiration

β†’ Complete Attribution & Dependencies
β†’ Implementation Origins & Code Attribution (Historical)


Contributing & Community

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