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HeliosDB Document Store User Guide

HeliosDB Document Store User Guide

Feature: F6.6 - MongoDB-Compatible Document Store Version: 1.0 Last Updated: November 2, 2025 Status: Production Ready

Overview

HeliosDB’s Document Store combines the flexibility of MongoDB with enterprise-grade features, offering true ACID transactions, sub-5ms query performance, and 120K writes/sec throughput. This guide has been split into modular sections for easier navigation.

Guide Sections

This comprehensive user guide is organized into the following sections:

1. Introduction

What you’ll learn:

  • What is a document store and why use it
  • HeliosDB Document Store vs MongoDB vs PostgreSQL JSONB
  • MongoDB wire protocol compatibility (80%)
  • PostgreSQL JSONB compatibility

Key highlights:

  • True ACID multi-document transactions
  • Sub-5ms query performance (P99)
  • 120K documents/sec write throughput
  • SQL integration and multi-model support

2. Quick Start (10 Minutes)

What you’ll learn:

  • Installation and setup
  • Creating your first collection
  • Basic CRUD operations
  • Running your first queries

Quick example:

// Insert a document
db.users.insertOne({ name: "Alice", age: 30, city: "NYC" });


// Query documents
db.users.find({ age: { $gt: 25 } });

3. CRUD Operations

What you’ll learn:

  • Insert: insertOne, insertMany, bulk inserts
  • Find: filters, projections, sorting, pagination
  • Update: updateOne, updateMany, replaceOne, upserts
  • Delete: deleteOne, deleteMany, bulk deletes

Topics covered:

  • Basic and advanced insert patterns
  • Query filters and operators
  • Update operators ($set, $inc, $push, $pull)
  • Atomic operations and transactions

4. Query Language

What you’ll learn:

  • Comparison operators ($eq, $gt, $lt, $in, $nin)
  • Logical operators ($and, $or, $not, $nor)
  • Array operators ($all, $elemMatch, $size)
  • Text search and geospatial queries
  • JSONPath and SQL queries

Query examples:

  • Complex filters with nested conditions
  • Array queries and element matching
  • Full-text search integration
  • Geospatial proximity queries

5. Indexing

What you’ll learn:

  • Index types: single-field, compound, multikey, text, geospatial
  • Creating and managing indexes
  • Query optimization with explain plans
  • Index strategies and best practices

Performance impact:

  • 100x+ speedup for indexed queries
  • Sub-5ms query latency (P99)
  • Efficient sorting and range scans

6. Aggregation Framework

What you’ll learn:

  • Aggregation pipeline stages
  • $match, $group, $project, $sort, $limit
  • $lookup (joins), $unwind (arrays)
  • Advanced aggregation patterns

Use cases:

  • Data analysis and reporting
  • Complex transformations
  • Multi-collection joins
  • Real-time analytics

7. Change Streams

What you’ll learn:

  • Real-time change notifications
  • Watching collections and databases
  • Filtering change events
  • Building reactive applications

Applications:

  • Real-time dashboards
  • Event-driven architectures
  • Data synchronization
  • Audit trails

8. Use Cases

Real-world examples:

  1. Content Management System - Flexible content types, versioning, media
  2. E-Commerce Product Catalog - Variant products, inventory, pricing
  3. User Profiles and Preferences - Personalization, settings, activity
  4. Event Logging and Analytics - High-volume writes, time-series queries
  5. Mobile App Backend - Offline sync, user data, push notifications
  6. Real-Time Collaboration - Change streams, concurrent editing, presence

Each use case includes complete schemas, queries, and integration code.

9. Performance Optimization

What you’ll learn:

  • Query optimization techniques
  • Index selection strategies
  • Bulk operation patterns
  • Performance monitoring

Benchmarks:

  • 120K inserts/sec (bulk)
  • Sub-5ms queries (indexed)
  • 50K concurrent connections

10. Integration

What you’ll learn:

  • MongoDB drivers (Node.js, Python, Java, Go, Rust)
  • SQL queries on documents
  • REST API integration
  • GraphQL integration

Language support:

  • JavaScript/TypeScript
  • Python
  • Java/Kotlin
  • Go
  • Rust
  • And more…

11. Migration from MongoDB

What you’ll learn:

  • Migration planning and assessment
  • Data export/import strategies
  • Application code changes
  • Performance comparison

Migration paths:

  • Direct MongoDB wire protocol (minimal changes)
  • mongodump/mongorestore tools
  • Application-level migration
  • Gradual transition strategies

12. API Reference

Complete reference:

  • Collection operations
  • Query operators
  • Update operators
  • Aggregation stages
  • Index operations
  • Transaction methods

Quick Reference

Key Features

FeaturePerformance
Write Throughput120K docs/sec (bulk)
Query Latency<5ms (P99, indexed)
TransactionsMulti-document ACID
MongoDB Compatibility80% wire protocol
Concurrent Connections50K+

Common Operations

// Insert
db.collection.insertOne({ field: "value" });


// Query
db.collection.find({ field: { $gt: 10 } });


// Update
db.collection.updateOne({ _id: id }, { $set: { field: "new value" } });


// Delete
db.collection.deleteMany({ status: "archived" });


// Aggregation
db.collection.aggregate([
  { $match: { status: "active" } },
  { $group: { _id: "$category", count: { $sum: 1 } } }
]);

Getting Help

Documentation Files

All sections of this guide are located in:

docs/guides/features/
├── DOCUMENT_STORE_USER_GUIDE.md (this index)
├── DOCUMENT_STORE_INTRO.md
├── DOCUMENT_STORE_QUICK_START.md
├── DOCUMENT_STORE_CRUD.md
├── DOCUMENT_STORE_QUERY_LANGUAGE.md
├── DOCUMENT_STORE_INDEXING.md
├── DOCUMENT_STORE_AGGREGATION.md
├── DOCUMENT_STORE_CHANGE_STREAMS.md
├── DOCUMENT_STORE_USE_CASES.md
├── DOCUMENT_STORE_PERFORMANCE.md
├── DOCUMENT_STORE_INTEGRATION.md
├── DOCUMENT_STORE_MIGRATION.md
└── DOCUMENT_STORE_API_REFERENCE.md

Start here: Introduction →