โšก Java 21 LTS Engine ๐Ÿง  HNSW Vector Search ๐Ÿ›ก๏ธ Full ACID Transactions ๐Ÿ“œ Apache 2.0 Open Source

The AI-Native Unified Database Engine

Stop stitching together PostgreSQL, Redis, Elasticsearch, Kafka, and Pinecone over high-latency network boundaries. SyntricDB unifies SQL, Vector Search, In-Memory Caching, Streaming, BM25 Full-Text, and Built-In AI SQL Functions into ONE zero-latency engine.

$ curl -fsSL https://raw.githubusercontent.com/upendra-manike/SyntricDB/main/deploy/mac/install_mac.sh | bash

SyntricDB Official Product Video

Watch the complete feature breakdown, 6-engine architecture, sub-millisecond HNSW vector benchmark, and multi-language SDK walkthrough.

SyntricDB in Action

Experience real-time performance, sub-millisecond HNSW vector search, and seamless single-engine architecture.

SyntricDB Studio Video Demo Showcase

๐ŸŽฌ Real-Time Interactive Studio Demo

Watch full tab-by-tab execution of SQL queries, vector embedding searches, and real-time transaction streaming.

SyntricDB Unified Architecture Flow Diagram

๐Ÿง  Unified 6-in-1 Engine Architecture

Single JVM process integrating HNSW Graph Vector Search, LSM-Tree Storage, In-Memory Caching, and Raft Replication.

SyntricDB vs Traditional Stack Comparison

โšก SyntricDB vs Traditional DB Sprawl

Eliminate network serialization overhead by replacing 5 separate infrastructure components with 1 database.

2026 AI Trends Vector Benchmark

๐Ÿ“ˆ Sub-Millisecond Vector Benchmark

Achieving <1.2ms ANN similarity search over 1,000,000 high-dimensional vector embeddings.

Built for Modern AI & Production Workloads

Engineered with high concurrency, ultra-low latency, and developer simplicity in mind.

๐Ÿง 

HNSW Vector Graph Engine

Native sub-millisecond Approximate Nearest Neighbor (ANN) search over high-dimensional embeddings using HNSW graph indices.

โšก

Java 21 Generational ZGC

Built on Java 21 LTS featuring sub-millisecond (<1ms) Garbage Collection pauses for multi-gigabyte memory pools.

๐Ÿ›ก๏ธ

Full ACID Transactions

Optimistic Concurrency Control (OCC) and Write-Ahead Logging (WAL) ensuring 100% data consistency and crash recovery.

๐Ÿ”

BM25 Full-Text Search

Inverted index engine supporting instant term relevance scoring, phrase matching, and fuzzy text queries.

๐Ÿ’พ

LSM-Tree Core Storage

Sequential WAL + SkipList MemTable + Immutable SSTables for lightning-fast disk write throughput.

๐ŸŒ

Distributed Raft Consensus

Zero-downtime cluster replication, automated leader election, and anti-entropy node synchronization.

Try SyntricDB SQL & Vector Commands

Click preset queries or type custom commands below to test the simulated engine.

syntricdb-cli โ€” v1.0.0 (Java 21 LTS / Netty 4)
โ— ONLINE
Preset Queries:
Welcome to SyntricDB Interactive Shell (connected to syntricdb://admin@localhost:8080/default)
Type 'HELP' or select a preset button above to execute sample queries.
syntricdb> SELECT id, title, AI_EMBED('wireless mouse') AS embedding FROM products WHERE embedding SIMILAR TO 'ergonomic mouse' TOP 3;
[ { "id": "prod_101", "title": "Logitech MX Master 3S Wireless Mouse", "similarity_score": 0.9642, "latency_ms": 0.84, "index_engine": "HNSW_L2_VECTOR_INDEX" }, { "id": "prod_104", "title": "Razer Basilisk Ultimate Wireless", "similarity_score": 0.8910, "latency_ms": 0.91, "index_engine": "HNSW_L2_VECTOR_INDEX" } ] -- Query executed in 0.84ms across 1,000,000 vectors
syntricdb>

Multi-Language Developer Integration Hub

Complete code examples and SDK guides for Python, Node.js, Java, Go, C#, Rust, PHP, Swift, Kotlin, Ruby, and REST API.

๐Ÿš€ Quickstart & One-Line Installers

SyntricDB can be installed instantly on macOS, Linux, Windows, Docker, or AWS EC2 using official single-command installers.

๐Ÿ macOS & Linux Terminal

bash
curl -fsSL https://raw.githubusercontent.com/upendra-manike/SyntricDB/main/deploy/mac/install_mac.sh | bash

๐ŸชŸ Windows 10 / 11 / Server (PowerShell)

powershell
powershell -ExecutionPolicy Bypass -Command "iwr -useb https://raw.githubusercontent.com/upendra-manike/SyntricDB/main/deploy/windows/install_windows.ps1 | iex"

๐Ÿณ Docker Container

docker
docker run -d -p 8080:8080 --name syntricdb syntricdb/syntricdb:latest

๐Ÿ”‘ Default Access Credentials

  • Username: admin
  • Password: syntricdb_secret_pass
  • URI: syntricdb://admin:syntricdb_secret_pass@localhost:8080/default
  • Web Dashboard: http://localhost:8080/
  • REST SQL API: http://localhost:8080/api/sql

๐Ÿ’ป CLI Utilization Guide (`syntricdb-cli`)

The SyntricDB Command Line Interface allows developers to manage tables, run SQL & AI vector queries, monitor cluster state, and stream WAL logs.

1. Interactive CLI Connection

bash
syntricdb-cli --host localhost --port 8080 --user admin --password syntricdb_secret_pass

2. Single Query Execution

bash
syntricdb-cli --exec "SELECT * FROM products WHERE embedding SIMILAR TO 'laptop' TOP 5;"

๐Ÿ“– Unified SQL & AI Function Reference

SyntricDB seamlessly blends ANSI SQL with AI Vector Search, BM25 scoring, and ACID transactions.

Vector Similarity Search

sql
SELECT id, title, price FROM products WHERE category = 'Electronics' AND embedding SIMILAR TO 'noise canceling headphones' TOP 5;

๐Ÿ Official Python Client SDK

Install via PyPI: pip install syntricdb-client

python
from syntricdb import SyntricDBClient client = SyntricDBClient(host="http://localhost:8080", api_key="syntricdb_secret_pass") # 1. Execute SQL Query res = client.query("SELECT * FROM products WHERE price < 100.00 LIMIT 10") print("SQL Results:", res) # 2. HNSW Vector Similarity Search vectors = client.vector_search(table="products", column="embedding", query="wireless gaming mouse", limit=3) print("Vector Matches:", vectors)

๐Ÿ’š Official Node.js / TypeScript Client SDK

Install via npm: npm install syntricdb-client

typescript
import { SyntricDBClient } from 'syntricdb-client'; const client = new SyntricDBClient({ endpoint: 'http://localhost:8080', username: 'admin', password: 'syntricdb_secret_pass' }); async function run() { const matches = await client.vectorSearch({ table: 'products', query: '4k gaming monitor', limit: 5 }); console.log('Top Vector Results:', matches); } run();

โ˜• Java & Spring Boot JPA Integration

Integrate SyntricDB into Spring Boot with zero extra dependencies using standard JPA Repositories.

java
@Repository public interface ProductRepository extends JpaRepository<Product, String> { @Query(value = "SELECT * FROM products WHERE category = :cat AND embedding SIMILAR TO :term TOP :limit", nativeQuery = true) List<Product> searchByVectorSimilarity(@Param("cat") String category, @Param("term") String searchTerm, @Param("limit") int limit); }

๐Ÿ”ท Go (Golang) Integration

go
package main import ( "bytes" "fmt" "net/http" ) func main() { jsonPayload := []byte(`{"sql": "SELECT * FROM products WHERE embedding SIMILAR TO 'mechanical keyboard' TOP 3"}`) req, _ := http.NewRequest("POST", "http://localhost:8080/api/sql", bytes.NewBuffer(jsonPayload)) req.Header.Set("Content-Type", "application/json") client := &http.Client{} resp, err := client.Do(req) if err == nil { fmt.Println("SyntricDB Response Code:", resp.StatusCode) } }

๐Ÿ’œ C# / .NET 8 Integration

csharp
using System.Net.Http.Json; var client = new HttpClient(); var payload = new { sql = "SELECT * FROM products WHERE embedding SIMILAR TO 'curved monitor' TOP 3" }; var response = await client.PostAsJsonAsync("http://localhost:8080/api/sql", payload); var result = await response.Content.ReadAsStringAsync(); Console.WriteLine(result);

๐Ÿฆ€ Rust Integration

rust
use reqwest::Client; use serde_json::json; #[tokio::main] async fn main() -> Result<(), Box<dyn std::error::Error>> { let client = Client::new(); let res = client.post("http://localhost:8080/api/sql") .json(&json!({ "sql": "SELECT * FROM products WHERE embedding SIMILAR TO 'mesh chair' TOP 3" })) .send() .await?; println!("SyntricDB Rust Result: {}", res.text().await?); Ok(()) }

๐Ÿ˜ PHP Integration

php
<?php $ch = curl_init('http://localhost:8080/api/sql'); $payload = json_encode(['sql' => "SELECT * FROM products WHERE embedding SIMILAR TO 'wireless headphones' TOP 3"]); curl_setopt($ch, CURLOPT_POSTFIELDS, $payload); curl_setopt($ch, CURLOPT_HTTPHEADER, ['Content-Type:application/json']); curl_setopt($ch, CURLOPT_RETURNTRANSFER, true); $result = curl_exec($ch); curl_close($ch); echo "SyntricDB PHP Output: " . $result; ?>

๐ŸŽ Swift (iOS / macOS) Integration

swift
import Foundation func querySyntricDB() async throws { let url = URL(string: "http://localhost:8080/api/sql")! var request = URLRequest(url: url) request.httpMethod = "POST" request.setValue("application/json", forHTTPHeaderField: "Content-Type") let json = ["sql": "SELECT * FROM products WHERE embedding SIMILAR TO 'macbook stand' TOP 3"] request.httpBody = try JSONSerialization.data(withJSONObject: json) let (data, _) = try await URLSession.shared.data(for: request) print("SyntricDB Swift Result:", String(data: data, encoding: .utf8)!) }

๐Ÿค– Kotlin (Android / JVM) Integration

kotlin
import okhttp3.* import okhttp3.MediaType.Companion.toMediaType import okhttp3.RequestBody.Companion.toRequestBody fun executeSyntricQuery() { val client = OkHttpClient() val mediaType = "application/json; charset=utf-8".toMediaType() val body = """{"sql": "SELECT * FROM products WHERE embedding SIMILAR TO 'smartwatch' TOP 3"}""".toRequestBody(mediaType) val request = Request.Builder() .url("http://localhost:8080/api/sql") .post(body) .build() client.newCall(request).execute().use { response -> println("SyntricDB Kotlin Result: ${response.body?.string()}") } }

๐Ÿ’Ž Ruby Integration

ruby
require 'net/http' require 'json' require 'uri' uri = URI.parse("http://localhost:8080/api/sql") header = {'Content-Type': 'application/json'} body = { sql: "SELECT * FROM products WHERE embedding SIMILAR TO 'mechanical pencil' TOP 3" } http = Net::HTTP.new(uri.host, uri.port) request = Net::HTTP::Post.new(uri.request_uri, header) request.body = body.to_json response = http.request(request) puts "SyntricDB Ruby Response: #{response.body}"

๐ŸŒ cURL & REST API Documentation

bash
curl -X POST http://localhost:8080/api/sql \ -H "Content-Type: application/json" \ -d '{"sql": "SELECT * FROM products WHERE embedding SIMILAR TO '\''wireless keyboard'\'' TOP 3;"}'

Download SyntricDB Packages

Get official SDK packages from PyPI, npm, Maven, or download the binary release.

๐Ÿ

Python Package

Official PyPI client package with built-in HNSW vector search support.

pip install syntricdb-client
๐Ÿ’š

Node.js Package

Official npm registry client library for JavaScript and TypeScript.

npm install syntricdb-client
๐Ÿ“ฆ

GitHub Source Code

Full open-source Java 21 codebase, benchmarks, and multi-language examples.

View on GitHub