Geode Overview

Geode is an enterprise-ready graph database that brings standards-based graph query capabilities with production-grade features, ACID guarantees, and high performance. Built from the ground up in Zig for memory safety and efficiency, Geode follows the ISO/IEC 39075:2024 100% GQL compliance and is designed for modern cloud-native deployments.

What is Geode?

Geode is a native graph database that stores and queries connected data using the property graph model. Unlike relational databases that use tables and expensive JOINs, Geode stores relationships as first-class primitives, enabling efficient multi-hop traversals and pattern matching queries that power social networks, recommendation engines, fraud detection systems, and knowledge graphs.

Key Differentiators

Standards-Based: ISO/IEC 39075:2024 compliance, ensuring no vendor lock-in and future-proof query language.

Production-Ready: 97.4% test coverage (1644/1688 tests), 100% GQL compliance (see conformance profile), rigorous governance with 1,735 CANARY markers tracking 2,190+ requirements.

Enterprise Features: Row-level security, audit logging, distributed transactions, savepoints, prepared statements, connection pooling.

High Performance: QUIC transport (HTTP/3 protocol), parallel query execution, native graph storage with index-free adjacency.

Modern Architecture: Memory-safe Zig implementation, QUIC + TLS 1.3 security, Protobuf wire protocol, polyglot client libraries.

Architecture

High-Level Design

┌───────────────────────────────────────────────────────────┐
│                     Client Layer                          │
│  ┌─────────┐  ┌─────────┐  ┌──────┐  ┌──────┐           │
│  │   Go    │  │ Python  │  │ Rust │  │ Zig  │  + more   │
│  └────┬────┘  └────┬────┘  └───┬──┘  └───┬──┘           │
└───────┼───────────┼───────────┼─────────┼───────────────┘
        │           │           │         │
        └───────────┴───────────┴─────────┘
         QUIC + TLS 1.3 (Port 3141)
┌───────────────────▼───────────────────────────────────────┐
│              Geode Server                                 │
│  ┌────────────────────────────────────────────────────┐   │
│  │         Protocol Layer (JSON Line Protocol)        │   │
│  └────────────────────┬───────────────────────────────┘   │
│                       │                                   │
│  ┌────────────────────▼───────────────────────────────┐   │
│  │              Query Engine                          │   │
│  │  ┌──────────┐  ┌────────┐  ┌─────────────┐        │   │
│  │  │  Parser  │→ │Optimizer│→ │  Executor   │        │   │
│  │  │  (GQL)   │  │         │  │ (Parallel)  │        │   │
│  │  └──────────┘  └────────┘  └─────────────┘        │   │
│  └────────────────────┬───────────────────────────────┘   │
│                       │                                   │
│  ┌────────────────────▼───────────────────────────────┐   │
│  │           Storage Engine                           │   │
│  │  ┌──────────────┐  ┌──────────┐  ┌─────────────┐  │   │
│  │  │ Graph Store  │  │  Indexes │  │     WAL     │  │   │
│  │  │ (Native)     │  │          │  │ (Durable)   │  │   │
│  │  └──────────────┘  └──────────┘  └─────────────┘  │   │
│  │  ┌──────────────┐  ┌──────────┐                   │   │
│  │  │ Transaction  │  │   RLS    │                   │   │
│  │  │   Manager    │  │  Engine  │                   │   │
│  │  └──────────────┘  └──────────┘                   │   │
│  └────────────────────────────────────────────────────┘   │
└───────────────────────────────────────────────────────────┘

Core Components

Protocol Layer:

  • QUIC transport for low-latency, encrypted communication
  • Protobuf wire protocol for language-independent messaging
  • TLS 1.3 for security by default
  • Connection pooling and multiplexing

Query Engine:

  • GQL parser implementing ISO/IEC 39075:2024
  • Cost-based query optimizer
  • Parallel execution engine (multi-core support)
  • Prepared statement caching

Storage Engine:

  • Native graph storage with adjacency lists
  • Index-free adjacency for O(1) traversals
  • B-tree indexes for property lookups
  • Write-ahead log (WAL) for durability
  • Row-level security (RLS) enforcement
  • Transaction management (ACID)

Core Features

Graph Query Language (GQL)

Geode follows the ISO/IEC 39075:2024 100% GQL compliance:

-- Pattern matching
MATCH (p:Person)-[:KNOWS*2..4]->(friend)
WHERE p.city = 'San Francisco'
RETURN friend.name, friend.city;

-- Aggregations
MATCH (u:User)-[:PURCHASED]->(p:Product)
RETURN p.category, count(u) AS buyers, sum(p.price) AS revenue
GROUP BY p.category
ORDER BY revenue DESC;

-- Temporal queries
MATCH (e:Event)
WHERE e.timestamp >= CURRENT_TIMESTAMP - DURATION 'P7D'
RETURN e.name, e.timestamp;

ACID Transactions

Full transaction support with distributed ACID guarantees:

BEGIN TRANSACTION;

-- Multiple operations
INSERT (order:Order {id: 'o123', total: 299.99});
MATCH (customer:Customer {id: 'c456'})
INSERT (customer)-[:PLACED]->(order);

-- Savepoints for partial rollback
SAVEPOINT sp1;

-- Risky operation
INSERT (payment:Payment {amount: 299.99});

-- Rollback to savepoint if needed
ROLLBACK TO SAVEPOINT sp1;

COMMIT;

Row-Level Security (RLS)

Fine-grained access control at the node and relationship level:

-- Define security policy
CREATE POLICY user_data_isolation ON User
  USING (id = current_user_id());

CREATE POLICY confidential_relationships ON MANAGES
  USING (current_user_role IN ['admin', 'manager']);

-- Automatically enforced on all queries
MATCH (u:User) RETURN u.name;  -- Only returns accessible users

High-Performance Indexing

Multiple index types for different query patterns:

-- B-tree indexes for equality and range queries
CREATE INDEX user_email ON User(email);
CREATE INDEX order_date ON Order(date);

-- Composite indexes
CREATE INDEX product_category_price ON Product(category, price);

-- Full-text search indexes
CREATE FULLTEXT INDEX product_search ON Product(name, description);

-- Use full-text search
MATCH (p:Product)
WHERE fulltext_search(p, 'wireless headphones bluetooth')
RETURN p.name, p.price;

Temporal Data Support

Native temporal types and operations:

-- Temporal data types
INSERT (event:Event {
  name: 'Conference',
  start: TIMESTAMP '2024-06-15 09:00:00-07:00',
  duration: DURATION 'PT8H',
  scheduled_date: DATE '2024-06-15'
});

-- Temporal queries
MATCH (e:Event)
WHERE e.start >= CURRENT_TIMESTAMP
  AND e.start <= CURRENT_TIMESTAMP + DURATION 'P30D'
RETURN e.name, e.start
ORDER BY e.start;

-- Time-series aggregations
MATCH (sale:Sale)
WHERE sale.timestamp >= DATE '2024-01-01'
RETURN
  date_trunc('month', sale.timestamp) AS month,
  count(*) AS sale_count,
  sum(sale.amount) AS revenue
GROUP BY month
ORDER BY month;

Use Cases

Social Networks

Model users, connections, posts, likes, and recommendations:

-- Friend suggestions (friends of friends)
MATCH (me:User {id: $user_id})-[:FRIEND]->(f1)-[:FRIEND]->(f2)
WHERE f2 <> me
  AND NOT EXISTS { MATCH (me)-[:FRIEND]->(f2) }
RETURN f2.name, count(f1) AS mutual_friends
ORDER BY mutual_friends DESC
LIMIT 10;

-- News feed generation
MATCH (me:User {id: $user_id})-[:FOLLOWS]->(author)-[:POSTED]->(post:Post)
WHERE post.created >= CURRENT_TIMESTAMP - DURATION 'P7D'
RETURN post, author.name
ORDER BY post.created DESC
LIMIT 50;

Recommendation Engines

Collaborative filtering and content-based recommendations:

-- Product recommendations (collaborative filtering)
MATCH (me:User {id: $user_id})-[:PURCHASED]->(p:Product)<-[:PURCHASED]-(similar:User)
MATCH (similar)-[:PURCHASED]->(rec:Product)
WHERE NOT EXISTS { MATCH (me)-[:PURCHASED]->(rec) }
RETURN rec.name, count(similar) AS recommendation_score
ORDER BY recommendation_score DESC
LIMIT 20;

-- Similar products (content-based)
MATCH (p:Product {id: $product_id})-[:IN_CATEGORY]->(cat:Category)<-[:IN_CATEGORY]-(similar:Product)
WHERE similar <> p
  AND abs(similar.price - p.price) < 50
RETURN similar.name, similar.price, similar.rating
ORDER BY similar.rating DESC;

Fraud Detection

Pattern matching for suspicious behavior:

-- Circular transaction patterns (money laundering)
MATCH path = (a:Account)-[:TRANSFER*3..5]->(a)
WHERE all(r IN relationships(path) WHERE r.amount > 10000)
  AND all(r IN relationships(path) WHERE r.timestamp >= CURRENT_DATE - DURATION 'P7D')
RETURN path,
  reduce(sum = 0, r IN relationships(path) | sum + r.amount) AS total_amount
ORDER BY total_amount DESC;

-- Velocity checks (rapid transfers)
MATCH (a:Account)-[t:TRANSFER]->(b:Account)
WHERE t.timestamp >= CURRENT_TIMESTAMP - DURATION 'PT1H'
WITH a, count(t) AS transfer_count, sum(t.amount) AS total_amount
WHERE transfer_count > 10 OR total_amount > 100000
RETURN a.id, transfer_count, total_amount
ORDER BY total_amount DESC;

Knowledge Graphs

Semantic networks and relationship discovery:

-- Entity relationships
MATCH (entity:Entity {name: 'Albert Einstein'})
      -[r1:RELATED_TO]->(related)
      -[r2:RELATED_TO]->(further)
RETURN
  entity.name,
  type(r1) AS relationship1,
  related.name,
  type(r2) AS relationship2,
  further.name
LIMIT 100;

-- Concept hierarchies
MATCH path = (specific:Concept)-[:IS_A*]->(general:Concept {name: 'Science'})
RETURN specific.name, length(path) AS distance_from_science
ORDER BY distance_from_science;

Infrastructure Management

Network dependencies and impact analysis:

-- Service dependency tree
MATCH path = (service:Service {name: 'web-api'})-[:DEPENDS_ON*]->(dependency)
RETURN path, length(path) AS depth
ORDER BY depth;

-- Impact analysis (what breaks if this fails?)
MATCH (failed:Server {id: 'srv-42'})<-[:DEPENDS_ON*]-(affected)
RETURN affected.name, affected.criticality, affected.users_affected
ORDER BY affected.criticality DESC;

Performance Characteristics

Query Performance

Traversals: O(1) per hop regardless of graph size (index-free adjacency) Lookups: O(log n) with indexes, O(n) without Aggregations: Parallelized across CPU cores Joins: Unnecessary (relationships are native)

Benchmarks

Query Types:

  • Short paths (1-2 hops)
  • Multi-hop paths with filters
  • Large aggregations
  • Batched bulk writes

Scalability

Distributed Deployment: Up to 32 shards with automatic coordination Concurrent Connections: Connection pooling supported Properties: Wide property sets supported (storage dependent)

Deployment Options

Standalone Server

Single-instance deployment for development and small production workloads:

# Start server
./geode serve --listen 0.0.0.0:3141 --data /var/lib/geode

# Configure
./geode serve --config /etc/geode/geode.conf

Docker Container

Containerized deployment for cloud environments:

# Pull image
docker pull geodedb/geode:latest

# Run container
docker run -d \
  -p 3141:3141 \
  -v /data/geode:/var/lib/geode \
  --name geode-server \
  geodedb/geode:latest

Kubernetes

Cloud-native orchestration:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: geode
spec:
  replicas: 3
  selector:
    matchLabels:
      app: geode
  template:
    metadata:
      labels:
        app: geode
    spec:
      containers:
      - name: geode
        image: geodedb/geode:latest
        ports:
        - containerPort: 3141
        volumeMounts:
        - name: data
          mountPath: /var/lib/geode

High Availability

Multi-instance deployment with replication (enterprise feature):

  • Master-replica replication
  • Automatic failover
  • Read replicas for scaling queries
  • Distributed transactions

Client Libraries

Supported Languages

Go: geodedb.com/geode

  • database/sql driver interface
  • Connection pooling
  • Prepared statements
  • Full type safety

Python: geode-client (PyPI)

  • Async/await with asyncio
  • Connection pooling
  • Type hints
  • RLS policy management

Rust: geode-client (crates.io)

  • Tokio-based async
  • Zero-cost abstractions
  • Type-safe builders
  • Connection pooling

Zig: Native client library

  • QUIC implementation included
  • Memory-safe
  • Zero dependencies
  • Example code included

Example: Go Client

package main

import (
    "context"
    "fmt"
    "log"
    _ "geodedb.com/geode"
    "database/sql"
)

func main() {
    db, err := sql.Open("geode", "quic://localhost:3141")
    if err != nil {
        log.Fatal(err)
    }
    defer db.Close()

    rows, err := db.QueryContext(context.Background(),
        "MATCH (p:Person) WHERE p.age > $age RETURN p.name, p.city",
        sql.Named("age", 30))
    if err != nil {
        log.Fatal(err)
    }
    defer rows.Close()

    for rows.Next() {
        var name, city string
        rows.Scan(&name, &city)
        fmt.Printf("%s from %s\n", name, city)
    }
}

Monitoring and Operations

Metrics

Geode exposes operational metrics:

  • Query latency (p50, p95, p99)
  • Throughput (queries/second)
  • Connection count
  • Transaction rate
  • Storage usage
  • Index hit rates

Logging

Structured logging with configurable levels:

2024-06-15T10:30:45Z [INFO] Query executed: duration=15ms
2024-06-15T10:30:46Z [WARN] Slow query detected: duration=2.5s query="MATCH..."
2024-06-15T10:30:47Z [ERROR] Transaction rollback: reason="constraint violation"

Backup and Restore

# Create backup
./geode backup --output /backups/geode-2024-06-15.tar.gz

# Restore from backup
./geode restore --input /backups/geode-2024-06-15.tar.gz

Security Features

Authentication

  • Username/password authentication
  • API key authentication
  • Integration with external auth providers (LDAP, OAuth)

Authorization

  • Row-level security (RLS) policies
  • Role-based access control (RBAC)
  • Fine-grained permissions per node/relationship type

Encryption

  • TLS 1.3 for all client connections (mandatory)
  • Encrypted storage at rest (optional)
  • Encrypted backups

Audit Logging

All data modifications logged with:

  • User identity
  • Timestamp
  • Query executed
  • Affected nodes/relationships

Comparison with Other Databases

vs. Neo4j

FeatureGeodeNeo4j
Query LanguageGQL (ISO standard)Cypher (proprietary)
ACIDFull distributed ACIDFull ACID (single instance)
RLSNativePlugin/application-level
LicensingApache 2.0 (open-source)Dual (GPL/commercial)
TransportQUIC (HTTP/3)Bolt protocol

vs. Amazon Neptune

FeatureGeodeAmazon Neptune
Query LanguageGQLGremlin, SPARQL
DeploymentAny cloud or on-premiseAWS only
CostOpen-sourcePay per instance-hour
StandardsISO GQLApache TinkerPop, W3C

vs. Relational (PostgreSQL)

FeatureGeodePostgreSQL
Data ModelProperty graphTables (relational)
RelationshipsFirst-classForeign keys + JOINs
Multi-hop queriesO(1) per hopO(n^hops)
SchemaFlexibleRigid
Use CaseConnected dataStructured tabular data

Community and Support

Open Source

  • Apache License 2.0
  • Public GitLab repository
  • Active issue tracker
  • Community contributions welcome

Documentation

  • Complete API reference
  • Tutorial and guides
  • Example applications
  • Video tutorials

Commercial Support

  • Enterprise support contracts
  • Training and consulting
  • Custom feature development
  • SLA guarantees

Roadmap

Current (v0.1.3)

  • 100% GQL compliance
  • Row-level security
  • Distributed transactions
  • Client libraries (Go, Python, Rust, Zig)

Upcoming

  • Distributed graph partitioning
  • Graph algorithms library (PageRank, community detection)
  • GraphQL API gateway
  • Streaming query results
  • Time-travel queries (temporal versioning)

Getting Started

Quick Start

# Install
curl -sSL https://geodedb.com/install.sh | sh

# Start server
geode serve

# Connect and query
geode shell
> INSERT (p:Person {name: 'Alice', age: 30});
> MATCH (p:Person) RETURN p.name, p.age;

Learn More

  • Tutorial: Step-by-step GQL guide
  • Documentation: Complete reference
  • Examples: Sample applications
  • Community: Forum and chat

Conclusion

Geode is a production-ready graph database that combines standards-based query language (ISO GQL), enterprise features (RLS, audit logging, distributed ACID), and high performance (QUIC transport, parallel execution) to power modern graph applications. Whether you’re building social networks, recommendation engines, fraud detection systems, or knowledge graphs, Geode provides the foundation for scalable, maintainable, and secure graph data management.

Explore the documentation below to dive deeper into specific features, use cases, and best practices.


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