BLite.Core 3.6.6

⚡ BLite

High-Performance BSON Database Engine for .NET

BLite is an embedded, ACID-compliant, document-oriented database built from scratch for maximum performance and zero allocation. It leverages modern .NET features like Span<T>, Memory<T>, and Source Generators to eliminate runtime overhead.

Compatibility: Targets net10.0 and netstandard2.1 — works with .NET 5+, Unity, Xamarin, MAUI, and any netstandard2.1-compatible runtime.

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🚀 Why BLite?

Most embedded databases for .NET are either wrappers around C libraries (SQLite, RocksDB) or legacy C# codebases burdened by heavy GC pressure.

BLite is different:

• Zero Allocation: I/O and interaction paths use Span<byte> and stackalloc. No heap allocations for reads/writes.
• Type-Safe: No reflection. All serialization code is generated at compile-time.
• Developer Experience: Full LINQ provider (IQueryable) that feels like Entity Framework but runs on bare metal.
• Reliable: Full ACID transactions with Write-Ahead Logging (WAL) and Snapshot Isolation.

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✨ Key Features

🚄 Zero-Allocation Architecture

• Span-based I/O: The entire pipeline, from disk to user objects, utilizes Span<T> to avoid copying memory.
• Memory-Mapped Files: OS-level paging and caching for blazing fast access.

🧠 Powerful Query Engine (LINQ)

Write queries naturally using LINQ. The engine automatically translates them to optimized B-Tree lookups.

// Automatic Index Usage
var users = collection.AsQueryable()
    .Where(x => x.Age > 25 && x.Name.StartsWith("A"))
    .OrderBy(x => x.Age)
    .Take(10)
    .AsEnumerable(); // Executed efficiently on the engine

• Optimized: Uses B-Tree indexes for =, >, <, Between, and StartsWith.
• Hybrid Execution: Combines storage-level optimization with in-memory LINQ to Objects.
• Advanced Features: Full support for GroupBy, Join, Select (including anonymous types), and Aggregations (Count, Sum, Min, Max, Average).

🔍 Advanced Indexing

• B-Tree Indexes: Logarithmic time complexity for lookups.
• Composite Indexes: Support for multi-column keys.
• Nested Property Indexes: Index on embedded sub-object fields using lambda expressions (x => x.Address.City) for typed collections, or dot-notation strings ("address.city") for schema-less collections. Intermediate null values are safely skipped.
• Vector Search (HNSW): Fast similarity search for AI embeddings using Hierarchical Navigable Small World algorithm.

🏷️ Secondary Indexes on Nested Properties (Typed Collections)

Configure secondary indexes on embedded sub-object properties using a standard lambda path in OnModelCreating:

protected override void OnModelCreating(ModelBuilder modelBuilder)
{
    // Index on a top-level property
    modelBuilder.Entity<Customer>()
        .HasIndex(x => x.Email);

    // Index on a nested property — dot-notation path is inferred automatically
    modelBuilder.Entity<Customer>()
        .HasIndex(x => x.Address.City);

    // Deeper nesting is supported too
    modelBuilder.Entity<Order>()
        .HasIndex(x => x.Shipping.Address.PostalCode);
}

// The index is then used automatically by the LINQ engine
var italianCustomers = db.Customers.AsQueryable()
    .Where(c => c.Address.City == "Milan")
    .ToList(); // → B-Tree index hit on "address.city"

Note: If an intermediate property is null (e.g. Address is null) the record is simply skipped by the indexer — no exception is thrown.

🔎 BLQL — BLite Query Language

MQL-inspired query language for schema-less (DynamicCollection) scenarios. Filter, sort, project, and page BsonDocument results using either a fluent C# API or JSON strings — no compile-time types required.

// JSON string entry-point (MQL-style)
var docs = col.Query("""{ "status": "active", "age": { "$gt": 18 } }""")
    .Sort("""{ "name": 1 }""")
    .Skip(0).Take(20)
    .ToList();

// Fluent C# API
var docs = col.Query()
    .Filter(BlqlFilter.And(
        BlqlFilter.Eq("status", "active"),
        BlqlFilter.Gt("age", 18)))
    .OrderBy("name")
    .Project(BlqlProjection.Include("name", "email"))
    .ToList();

• Comparison: $eq, $ne, $gt, $gte, $lt, $lte, $in, $nin, $exists, $type, $regex.
• String: $startsWith, $endsWith, $contains — ordinal comparison, no regex interpretation.
• Array: $elemMatch (scalar and document arrays), $size, $all.
• Arithmetic: $mod — modulo check with zero-divisor protection at parse time.
• Logical: $and, $or, $nor, $not (top-level) and $not (field-level condition negation). Implicit AND for multiple top-level fields.
• Geospatial: $geoWithin (bounding box) and $geoNear (Haversine radius in km).
• Vector: $nearVector — index-accelerated ANN search via HNSW.
• Security-hardened: Unknown $ operators throw FormatException. Every operator validates its JSON type. $mod divisor=0 rejected at parse time. ReDoS protected via NonBacktracking. 252 dedicated security tests.

🤖 AI-Ready Vector Search

BLite natively supports vector embeddings and fast similarity search.

// 1. Configure vector index on float[] property
modelBuilder.Entity<VectorItem>()
    .HasVectorIndex(x => x.Embedding, dimensions: 1536, metric: VectorMetric.Cosine);

// 2. Perform fast similarity search
var results = db.Items.AsQueryable()
    .VectorSearch(x => x.Embedding, queryVector, k: 5)
    .ToList();

v3.6.2 HNSW correctness: the HNSW implementation received a full correctness pass — AllocateNode overflow, neighbor link integrity (LinkPageChain), SelectNeighbors heuristic (keep closest, not farthest), random level distribution (mL = 1/ln(M)), and persistence across database close/reopen are all fixed.

🛠️ Vector Source Configuration (RAG Optimization)

For sophisticated RAG (Retrieval-Augmented Generation) scenarios, BLite allows you to define a Vector Source Configuration directly on the collection metadata. This configuration specifies which BSON fields should be used to build the input text for your embedding model.

// Define which fields to include in the normalized text for embedding
var config = new VectorSourceConfig()
    .Add("title",   weight: 2.0)   // Boost important fields
    .Add("content", weight: 1.0)
    .Add("tags",    weight: 0.5);

// Set it on a collection
engine.SetVectorSource("documents", config);

// Use TextNormalizer to build the text from any BsonDocument
string text = TextNormalizer.BuildEmbeddingText(doc, config);
// -> "TITLE [Boost: 2.0] ... CONTENT ... TAGS [Boost: 0.5] ..."

🌍 High-Performance Geospatial Indexing

BLite features a built-in R-Tree implementation for lightning-fast proximity and bounding box searches.

• Zero-Allocation: Uses coordinate tuples (double, double) and Span-based BSON arrays.
• LINQ Integrated: Search naturally using .Near() and .Within().

// 1. Configure spatial index (uses R-Tree internally)
modelBuilder.Entity<Store>()
    .HasSpatialIndex(x => x.Location);

// 2. Proximity Search (Find stores within 5km)
var stores = db.Stores.AsQueryable()
    .Where(s => s.Location.Near((45.4642, 9.1899), 5.0))
    .ToList();

// 3. Bounding Box Search
var area = db.Stores.AsQueryable()
    .Where(s => s.Location.Within((45.0, 9.0), (46.0, 10.0)))
    .ToList();

🆔 Custom ID Converters (ValueObjects)

Native support for custom primary key types using ValueConverter<TModel, TProvider>. Configure them easily via the Fluent API.

// 1. Define your ValueObject and Converter
public record OrderId(string Value);
public class OrderIdConverter : ValueConverter<OrderId, string> { ... }

// 2. Configure in OnModelCreating
modelBuilder.Entity<Order>()
    .Property(x => x.Id)
    .HasConversion<OrderIdConverter>();

// 3. Use it naturally
var order = collection.FindById(new OrderId("ORD-123"));

📡 Change Data Capture (CDC)

Real-time event streaming for database changes with transactional consistency.

• Zero-Allocation: Events are only captured when watchers exist; no overhead when disabled.
• Transactional: Events fire only after successful commit, never on rollback.
• Scalable: Uses Channel-per-subscriber architecture to support thousands of concurrent listeners.

// Watch for changes in a collection
using var subscription = db.People.Watch(capturePayload: true)
    .Subscribe(e => 
    {
        Console.WriteLine($"{e.Type}: {e.DocumentId}");
        if (e.Entity != null) 
            Console.WriteLine($"  Name: {e.Entity.Name}");
    });

// Perform operations - events fire after commit
db.People.Insert(new Person { Id = 1, Name = "Alice" });

// v3.6.0 — DynamicCollection.Watch() is also supported
using var dynSub = engine.GetOrCreateCollection("orders").Watch()
    .Subscribe(e => Console.WriteLine($"{e.Type}: {e.DocumentId}"));

🛡️ Transactions & ACID

• Atomic: Multi-document transactions.
• Durable: WAL ensures data safety even in power loss.
• Isolated: Snapshot isolation allowing concurrent readers and writers.
• Thread-Safe: Protected with SemaphoreSlim to prevent race conditions in concurrent scenarios.
• Async-First: Full async/await support across reads, writes, and transactions.
• Implicit Transactions: Use SaveChanges() / SaveChangesAsync() for automatic transaction management.

� Native TimeSeries

A dedicated PageType.TimeSeries — an append-only page format optimised for high-throughput time-ordered data. Introduced natively in 1.12; the typed DocumentDbContext fluent API (HasTimeSeries) was added in 3.3.0.

• No background threads: pruning fires transparently on insert (every 1 000 docs or 5 min).
• Page-level granularity: entire expired pages are freed in a single pass — O(freed pages), not O(all documents).
• Transparent reads: FindAll(), BLQL queries, and B-Tree lookups work unchanged.

// Enable on any DynamicCollection
var sensors = engine.GetOrCreateCollection("sensors");
sensors.SetTimeSeries("timestamp", TimeSpan.FromDays(7));
engine.Commit();

// Insert as normal — routing to TS pages is automatic
var doc = sensors.CreateDocument(
    ["deviceId", "temperature", "timestamp"],
    b => b.Set("deviceId", "sensor-42")
          .Set("temperature", 23.5)
          .Set("timestamp", DateTime.UtcNow));
sensors.Insert(doc);

// Force prune immediately (useful in tests)
sensors.ForcePrune();

Typed API (DocumentDbContext — added in 3.3.0)

Configure a typed collection as TimeSeries in OnModelCreating using HasTimeSeries:

protected override void OnModelCreating(ModelBuilder modelBuilder)
{
    modelBuilder.Entity<SensorReading>()
        .ToCollection("sensor_readings")
        .HasTimeSeries(r => r.Timestamp, retention: TimeSpan.FromDays(7));
}

// Insert as normal — routing to TS pages is automatic
db.SensorReadings.Insert(new SensorReading
{
    SensorId  = "sensor-42",
    Value     = 23.5,
    Timestamp = DateTime.UtcNow
});
db.SaveChanges();

// Force prune (useful in tests / maintenance)
db.SensorReadings.ForcePrune();

�🔄 Hot Backup

BLite supports hot backups of live databases without blocking readers. The engine uses a combination of the commit lock and WAL checkpointing to ensure the backup is a fully consistent, standalone database file.

// 1. Embedded mode (DocumentDbContext)
await db.BackupAsync("backups/mydb-2026-02-25.blite", cancellationToken);

// 2. Schema-less mode (BLiteEngine)
await engine.BackupAsync("backups/mydb-backup.blite");

⚡ Async Read Operations

All read paths have a true async counterpart — cancellation is propagated all the way down to OS-level RandomAccess.ReadAsync (IOCP on Windows).

// FindById — async primary-key lookup via B-Tree
var order = await db.Orders.FindByIdAsync(id, ct);

// FindAll — async streaming (IAsyncEnumerable)
await foreach (var order in db.Orders.FindAllAsync(ct))
    Process(order);

// FindAsync — async predicate scan (IAsyncEnumerable)
await foreach (var order in db.Orders.FindAsync(o => o.Status == "shipped", ct))
    Process(order);

// LINQ — full async materialisation
var shipped = await db.Orders
    .AsQueryable()
    .Where(o => o.Status == "shipped")
    .ToListAsync(ct);

// Async aggregates
int count = await db.Orders.AsQueryable().CountAsync(ct);
bool any  = await db.Orders.AsQueryable().AnyAsync(o => o.Total > 500, ct);
bool all  = await db.Orders.AsQueryable().AllAsync(o => o.Currency == "EUR", ct);

// First/Single helpers
var first  = await db.Orders.AsQueryable().FirstOrDefaultAsync(o => o.Status == "pending", ct);
var single = await db.Orders.AsQueryable().SingleOrDefaultAsync(o => o.Id == id, ct);

// Materialise to array
var arr = await db.Orders.AsQueryable().ToArrayAsync(ct);

// SaveChanges is also async
await db.SaveChangesAsync(ct);

Available async read methods on DocumentCollection<TId, T>:

Method	Description
FindByIdAsync(id, ct)	Primary-key lookup via B-Tree; returns ValueTask<T?>
FindAllAsync(ct)	Full collection streaming; returns IAsyncEnumerable<T>
FindAsync(predicate, ct)	Async predicate scan; returns IAsyncEnumerable<T>
AsQueryable().ToListAsync(ct)	LINQ pipeline materialized as Task<List<T>>
AsQueryable().ToArrayAsync(ct)	LINQ pipeline materialized as Task<T[]>
AsQueryable().FirstOrDefaultAsync(ct)	First match or null
AsQueryable().SingleOrDefaultAsync(ct)	Single match or null; throws on duplicates
AsQueryable().CountAsync(ct)	Element count
AsQueryable().AnyAsync(predicate, ct)	Short-circuits on first match
AsQueryable().AllAsync(predicate, ct)	Returns false on first non-match

🔌 Intelligent Source Generation

• Zero Reflection: Mappers are generated at compile-time for zero overhead.
• Nested Objects & Collections: Full support for complex graphs, deep nesting, and ref struct handling.
• Robust Serialization: Correctly handles nested objects, collections, and complex type hierarchies.
• Lowercase Policy: BSON keys are automatically persisted as lowercase for consistency.
• Custom Overrides: Use [BsonProperty] or [JsonPropertyName] for manual field naming.

✅ Supported Scenarios

The source generator handles a wide range of modern C# patterns:

Feature	Support	Description
Property Inheritance	✅	Properties from base classes are automatically included in serialization
Private Setters	✅	Properties with private set are correctly deserialized using Expression Trees
Init-Only Setters	✅	Properties with init are supported via runtime compilation
Private Constructors	✅	Deserialization works even without parameterless public constructor
Advanced Collections	✅	IEnumerable<T>, ICollection<T>, IList<T>, HashSet<T>, and more
Nullable Value Types	✅	ObjectId?, int?, DateTime? are correctly serialized/deserialized
Nullable Collections	✅	List<T>?, string? with proper null handling
Unlimited Nesting	✅	Deeply nested object graphs with circular reference protection
Self-Referencing	✅	Entities can reference themselves (e.g., Manager property in Employee). Schema generation is recursion-safe — cycles are detected and terminated automatically
N-N Relationships	✅	Collections of ObjectIds for efficient document referencing

❌ Limitations & Design Choices

Scenario	Status	Reason
Computed Properties	⚠️ Excluded	Getter-only properties without backing fields are intentionally skipped (e.g., FullName => $"{First} {Last}")
Constructor Logic	⚠️ Bypassed	Deserialization uses FormatterServices.GetUninitializedObject() to avoid constructor execution
Constructor Validation	⚠️ Not Executed	Validation logic in constructors won't run during deserialization - use Data Annotations instead

💡 Best Practice: For relationships between entities, prefer referencing (storing ObjectIds) over embedding (full nested objects) to avoid data duplication and maintain consistency. See tests in CircularReferenceTests.cs for implementation patterns.

🏷️ Supported Attributes

BLite supports standard .NET Data Annotations for mapping and validation:

Attribute	Category	Description
[Table("name")]	Mapping	Sets the collection name. Supports Schema="s" for s.name grouping.
[Column("name")]	Mapping	Maps property to a specific BSON field name.
[Column(TypeName="...")]	Mapping	Handles special types (e.g., geopoint for coordinate tuples).
[Key]	Identity	Explicitly marks the primary key (maps to _id).
[NotMapped]	Mapping	Excludes property from BSON serialization.
[Required]	Validation	Ensures string is not null/empty or nullable type is not null.
[StringLength(max)]	Validation	Validates string length (supports MinimumLength).
[MaxLength(n)]	Validation	Validates maximum string length.
[MinLength(n)]	Validation	Validates minimum string length.
[Range(min, max)]	Validation	Validates numeric values stay within the specified range.

� IDocumentCollection<TId, T> Abstraction (v3.5.0)

Typed collections implement the IDocumentCollection<TId, T> interface — a clean contract covering full CRUD, bulk operations, LINQ, and async methods. This makes constructor injection and unit-test mocking straightforward without binding to the concrete DocumentCollection class.

// Inject or mock via the interface
public class OrderService
{
    private readonly IDocumentCollection<ObjectId, Order> _orders;

    public OrderService(IDocumentCollection<ObjectId, Order> orders) 
        => _orders = orders;

    public void Place(Order o) { _orders.Insert(o); }
}

�🗝️ Embedded Key-Value Store

BLite 3.2.0 ships a persistent key-value store co-located in the same database file — no extra process, no extra file. Access it via IBLiteKvStore on any BLiteEngine or DocumentDbContext.

• Raw bytes: values are byte[] / ReadOnlySpan<byte> — serialize however you like.
• Optional TTL: per-entry expiry with lazy purge (PurgeExpired()) or auto-purge on open.
• Prefix scan: enumerate all keys with a given prefix.
• Atomic batches: set + delete multiple keys under a single lock acquisition.

using var engine = new BLiteEngine("data.db");
IBLiteKvStore kv = engine.KvStore;

// Write (optional TTL)
kv.Set("session:abc", Encoding.UTF8.GetBytes("payload"), TimeSpan.FromHours(1));

// Read
byte[]? value = kv.Get("session:abc");

// Exists / Delete
bool exists = kv.Exists("session:abc");
kv.Delete("session:abc");

// Refresh expiry without rewriting value
kv.Refresh("session:abc", TimeSpan.FromHours(2));

// Prefix scan
IEnumerable<string> sessionKeys = kv.ScanKeys("session:");

// Atomic batch (one lock)
kv.Batch()
  .Set("k1", data1)
  .Set("k2", data2, TimeSpan.FromMinutes(30))
  .Delete("k3")
  .Execute();

// Options (passed to BLiteEngine / DocumentDbContext constructor)
var options = new BLiteKvOptions
{
    DefaultTtl         = TimeSpan.FromDays(1),
    PurgeExpiredOnOpen = true
};
using var db = new MyDbContext("app.db", options);
IBLiteKvStore kv = db.KvStore;

🚀 BLite.Caching — IDistributedCache

BLite.Caching wraps the embedded KV store as a fully compliant IDistributedCache — drop it in anywhere you'd use Redis or SQL Server cache, with zero external dependencies.

dotnet add package BLite.Caching

// ASP.NET Core DI registration
builder.Services.AddBLiteDistributedCache("cache.db");

// Optionally with KV options
builder.Services.AddBLiteDistributedCache("cache.db", new BLiteKvOptions
{
    DefaultTtl         = TimeSpan.FromMinutes(30),
    PurgeExpiredOnOpen = true
});

The package also exposes IBLiteCache — a typed superset of IDistributedCache:

// Typed helpers (uses System.Text.Json internally)
await cache.SetAsync("user:42", myUser, new DistributedCacheEntryOptions
{
    SlidingExpiration = TimeSpan.FromMinutes(20)
});

User? user = await cache.GetAsync<User>("user:42");

// GetOrSet — built-in thundering-herd protection (per-key SemaphoreSlim)
User user = await cache.GetOrSetAsync("user:42",
    factory: async ct => await db.LoadUserAsync(42, ct),
    options: new DistributedCacheEntryOptions { AbsoluteExpirationRelativeToNow = TimeSpan.FromHours(1) });

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📚 Documentation

📖 Official Documentation → blitedb.com/docs/getting-started

For in-depth technical details, see the complete specification documents:

• RFC.md - Full architectural specification covering storage engine, indexing, transactions, WAL protocol, and query processing
• C-BSON.md - Detailed wire format specification for BLite's Compressed BSON format, including hex dumps and performance analysis

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📦 Quick Start

1. Installation

dotnet add package BLite

2. Basic Usage

// 1. Define your Entities
public class User 
{ 
    public ObjectId Id { get; set; } 
    public string Name { get; set; } 
}

// 2. Define your DbContext (Source Generator will produce InitializeCollections)
public partial class MyDbContext : DocumentDbContext
{
    public DocumentCollection<ObjectId, User> Users { get; set; } = null!;

    public MyDbContext(string path) : base(path) 
    {
        InitializeCollections();
    }
}

// 3. Use with Implicit Transactions (Recommended)
using var db = new MyDbContext("mydb.db");

// Operations are tracked automatically
db.Users.Insert(new User { Name = "Alice" });
db.Users.Insert(new User { Name = "Bob" });

// Commit all changes at once
db.SaveChanges();

// 4. Query naturally with LINQ
var results = db.Users.AsQueryable()
    .Where(u => u.Name.StartsWith("A"))
    .AsEnumerable();

// 5. Or use explicit transactions for fine-grained control
using (var txn = db.BeginTransaction())
{
    db.Users.Insert(new User { Name = "Charlie" });
    txn.Commit(); // Explicit commit
}

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� Schema-less API (BLiteEngine / DynamicCollection)

When compile-time types are not available — server-side query processing, scripting, migrations, or interop scenarios — BLite exposes a fully schema-less BSON API via BLiteEngine and DynamicCollection.

Both paths share the same kernel: StorageEngine, B-Tree, WAL, Vector / Spatial indexes.

Entry Point

using var engine = new BLiteEngine("data.db");

// Open (or create) a schema-less collection
var orders = engine.GetOrCreateCollection("orders", BsonIdType.ObjectId);

// List all collections
IReadOnlyList<string> names = engine.ListCollections();

// Drop a collection
engine.DropCollection("orders");

Insert

// Build a BsonDocument using the engine's field-name dictionary
var doc = orders.CreateDocument(
    ["status", "total", "currency"],
    b => b
        .Set("status",   "pending")
        .Set("total",    199.99)
        .Set("currency", "EUR"));

BsonId id = orders.Insert(doc);

// Async variant
BsonId id = await orders.InsertAsync(doc, ct);

// Bulk insert (single transaction)
List<BsonId> ids = orders.InsertBulk([doc1, doc2, doc3]);
List<BsonId> ids = await orders.InsertBulkAsync([doc1, doc2, doc3], ct);

Read

// Primary-key lookup
BsonDocument? doc = orders.FindById(id);
BsonDocument? doc = await orders.FindByIdAsync(id, ct);

// Full scan
foreach (var d in orders.FindAll()) { ... }
await foreach (var d in orders.FindAllAsync(ct)) { ... }

// Predicate filter
var pending = orders.Find(d => d.GetString("status") == "pending");
await foreach (var d in orders.FindAsync(d => d.GetString("status") == "pending", ct)) { ... }

// Zero-copy predicate scan (BsonSpanReader — no heap allocation per document)
var pending = orders.Scan(reader =>
{
    // Read "status" field directly from the BSON bytes
    if (reader.TryReadString("status", out var status))
        return status == "shipped";
    return false;
});

// B-Tree range query on a secondary index
var recent = orders.QueryIndex("idx_placed_at", minDate, maxDate);

// Vector similarity search
var similar = orders.VectorSearch("idx_embedding", queryVector, k: 10);

// Geospatial proximity / bounding box
var nearby = orders.Near("idx_location", (45.46, 9.18), radiusKm: 5.0);
var inArea  = orders.Within("idx_location", (45.0, 9.0), (46.0, 10.0));

// Count
int total = orders.Count();

Update & Delete

bool updated = orders.Update(id, newDoc);
bool deleted = orders.Delete(id);

// Async (collection-level)
bool updated = await orders.UpdateAsync(id, newDoc, ct);
bool deleted = await orders.DeleteAsync(id, ct);

// Bulk (single transaction)
int updatedCount = orders.UpdateBulk([(id1, doc1), (id2, doc2)]);
int deletedCount = orders.DeleteBulk([id1, id2, id3]);

// Bulk async
int updatedCount = await orders.UpdateBulkAsync([(id1, doc1), (id2, doc2)], ct);
int deletedCount = await orders.DeleteBulkAsync([id1, id2, id3], ct);

// or via engine shortcuts (async)
await engine.UpdateAsync("orders", id, newDoc, ct);
await engine.DeleteAsync("orders", id, ct);
int u = await engine.UpdateBulkAsync("orders", [(id1, d1), (id2, d2)], ct);
int d = await engine.DeleteBulkAsync("orders", [id1, id2], ct);

Index Management

// B-Tree secondary index
orders.CreateIndex("status");                         // default name = "idx_status"
orders.CreateIndex("placed_at", unique: false);

// Unique index
orders.CreateIndex("order_number", unique: true);

// Nested path index (dot-notation) — indexes a field inside an embedded document
orders.CreateIndex("shipping.city");                  // indexes doc["shipping"]["city"]
orders.CreateIndex("customer.address.zip");           // arbitrary depth; null intermediates skipped

// Vector index (HNSW) — supports nested paths too
orders.CreateVectorIndex("embedding", dimensions: 1536, metric: VectorMetric.Cosine);
orders.CreateVectorIndex("meta.embedding", dimensions: 768, metric: VectorMetric.Cosine);

// Spatial index (R-Tree) — supports nested paths too
orders.CreateSpatialIndex("location");
orders.CreateSpatialIndex("store.location");

// Introspect
IReadOnlyList<string> indexes = orders.ListIndexes();

// Drop
orders.DropIndex("idx_status");

Reading BsonDocument fields

BsonDocument? doc = orders.FindById(id);
if (doc is not null)
{
    string status   = doc.GetString("status");
    double total    = doc.GetDouble("total");
    BsonId docId    = doc.Id;
}

When to use which API

	DocumentDbContext	BLiteEngine
Type safety	✅ Compile-time	❌ Runtime BsonDocument
Source generators	✅ Zero reflection	—
LINQ	✅ Full IQueryable	❌
BLQL	❌	✅ JSON string queries
Schema-less / dynamic	❌	✅
Server / scripting mode	❌	✅
Performance	✅ Max (generated mappers)	✅ Near-identical (same kernel)
Shared storage	✅	✅ Same file

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🔎 BLQL — BLite Query Language

BLQL is a BLite Query Language for DynamicCollection — the schema-less counterpart of LINQ for DocumentDbContext. Inspired by MQL (MongoDB Query Language), it lets you filter, sort, project, and page BsonDocument results using JSON strings or a fluent C# API, with no compile-time type information required.

Entry Points

using BLite.Core.Query.Blql;

// 1. JSON string filter (MQL-style)
var docs = col.Query("""{ "status": "active", "age": { "$gt": 18 } }""")
    .Sort("""{ "name": 1 }""")
    .Skip(0).Take(20)
    .ToList();

// 2. Programmatic filter
var docs = col.Query()
    .Filter(BlqlFilter.Eq("status", "active").AndAlso(BlqlFilter.Gt("age", 18)))
    .OrderByDescending("createdAt")
    .Project(BlqlProjection.Include("name", "email", "createdAt"))
    .ToList();

Supported Filter Operators

Comparison & field tests

JSON syntax	C# equivalent	Description
{ "f": value }	BlqlFilter.Eq("f", v)	Equality
{ "f": { "$ne": v } }	BlqlFilter.Ne("f", v)	Not equal
{ "f": { "$gt": v } }	BlqlFilter.Gt("f", v)	Greater than
{ "f": { "$gte": v } }	BlqlFilter.Gte("f", v)	Greater than or equal
{ "f": { "$lt": v } }	BlqlFilter.Lt("f", v)	Less than
{ "f": { "$lte": v } }	BlqlFilter.Lte("f", v)	Less than or equal
{ "f": { "$in": [...] } }	BlqlFilter.In("f", ...)	Value in set
{ "f": { "$nin": [...] } }	BlqlFilter.Nin("f", ...)	Value not in set
{ "f": { "$exists": true } }	BlqlFilter.Exists("f")	Field exists
{ "f": { "$type": 16 } }	BlqlFilter.Type("f", BsonType.Int32)	BSON type check
{ "f": { "$regex": "^Al" } }	BlqlFilter.Regex("f", "^Al")	Regex (NonBacktracking)

String operators

JSON syntax	C# equivalent	Description
{ "f": { "$startsWith": "Al" } }	BlqlFilter.StartsWith("f", "Al")	Prefix match (ordinal)
{ "f": { "$endsWith": ".com" } }	BlqlFilter.EndsWith("f", ".com")	Suffix match (ordinal)
{ "f": { "$contains": "foo" } }	BlqlFilter.Contains("f", "foo")	Substring match (ordinal)

Array operators

JSON syntax	C# equivalent	Description
{ "f": { "$elemMatch": { "$gt": 80 } } }	BlqlFilter.ElemMatch("f", BlqlFilter.Gt("f", 80))	Any element satisfies condition
{ "f": { "$size": 3 } }	BlqlFilter.Size("f", 3)	Array has exact length
{ "f": { "$all": ["a", "b"] } }	BlqlFilter.All("f", ...)	Array contains all values

Arithmetic

JSON syntax	C# equivalent	Description
{ "f": { "$mod": [3, 0] } }	BlqlFilter.Mod("f", 3, 0)	field % divisor == remainder

Logical

JSON syntax	C# equivalent	Description
{ "$and": [...] }	BlqlFilter.And(...)	Logical AND
{ "$or": [...] }	BlqlFilter.Or(...)	Logical OR
{ "$nor": [...] }	BlqlFilter.Nor(...)	Logical NOR
{ "$not": {...} }	BlqlFilter.Not(...)	Top-level NOT
{ "f": { "$not": { "$gt": 0 } } }	BlqlFilter.Not(BlqlFilter.Gt("f", 0))	Field-level condition negation

Geospatial

JSON syntax	C# equivalent	Description
{ "loc": { "$geoWithin": { "$box": [[minLon,minLat],[maxLon,maxLat]] } } }	BlqlFilter.GeoWithin("loc", minLon, minLat, maxLon, maxLat)	Point inside bounding box
{ "loc": { "$geoNear": { "$center": [lon,lat], "$maxDistance": km } } }	BlqlFilter.GeoNear("loc", lon, lat, km)	Point within radius (Haversine)

Vector search

JSON syntax	C# equivalent	Description
{ "emb": { "$nearVector": { "$vector": [...], "$k": 10, "$metric": "cosine" } } }	BlqlFilter.NearVector("emb", vector, k: 10)	HNSW ANN similarity search

Multiple top-level fields in one JSON object produce an implicit AND:

{ "status": "active", "age": { "$gt": 18 } }

Sorting

// JSON sort (1 = ascending, -1 = descending)
var results = col.Query(filter)
    .Sort("""{ "lastName": 1, "age": -1 }""")  // multi-key sort
    .ToList();

// Fluent sort
var results = col.Query(filter)
    .OrderBy("lastName")
    .ToList();

Projection

// Include only specified fields
var results = col.Query(filter)
    .Project(BlqlProjection.Include("name", "email"))
    .ToList();

// Exclude specified fields
var results = col.Query(filter)
    .Project(BlqlProjection.Exclude("password", "__internal"))
    .ToList();

Paging & Terminal Methods

var page = col.Query(filter)
    .OrderBy("createdAt")
    .Skip(20).Take(10)     // or .Limit(10)
    .ToList();

// Single document
BsonDocument? doc = col.Query(filter).FirstOrDefault();

// Aggregates
int total = col.Query(filter).Count();
bool any  = col.Query(filter).Any();
bool none = col.Query(filter).None();

// Async streaming
await foreach (var doc in col.Query(filter).AsAsyncEnumerable(ct))
    Process(doc);

Security

The JSON parser is hardened against BLQL-injection:

• Unknown $ operators ($where, $expr, $function, …) → FormatException — never passed through.
• Every operator validates its JSON type (e.g. $startsWith requires string, $mod requires [divisor, remainder]) → FormatException on mismatch.
• $mod with divisor 0 is rejected at parse time, preventing DivideByZeroException at evaluation.
• $regex compiled with RegexOptions.NonBacktracking (ReDoS-safe). String operators ($startsWith, $endsWith, $contains) use ordinal comparison — regex metacharacters are literals.
• Deeply nested JSON (> 64 levels) is rejected by System.Text.Json before evaluation.
• 252 security tests covering type-confusion, division-by-zero, deep nesting DoS, large $in/$all array DoS, and vector dimension bombing.

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�🗺️ Roadmap & Status

We are actively building the core. Here is where we stand:

• ✅ Core Storage: Paged I/O, WAL, Transactions with thread-safe concurrent access.
• ✅ BSON Engine: Zero-copy Reader/Writer with lowercase policy.
• ✅ Indexing: B-Tree implementation.
• ✅ Vector Search: HNSW implementation for Similarity Search.
• ✅ Geospatial Indexing: Optimized R-Tree with zero-allocation tuple API.
• ✅ Query Engine: Hybrid execution (Index/Scan + LINQ to Objects).
• ✅ Advanced LINQ: GroupBy, Joins, Aggregations, Complex Projections.
• ✅ Async I/O: True async reads and writes — FindByIdAsync, FindAllAsync (IAsyncEnumerable<T>), ToListAsync/ToArrayAsync/CountAsync/AnyAsync/AllAsync/FirstOrDefaultAsync/SingleOrDefaultAsync for LINQ pipelines, SaveChangesAsync. CancellationToken propagates to RandomAccess.ReadAsync (IOCP on Windows).
• ✅ Source Generators: Auto-map POCO/DDD classes with robust nested objects, collections, and ref struct support. Self-referencing types (recursive cycles) are handled safely.
• ✅ Nested Property Indexes: Index on embedded sub-object fields via lambda paths (x => x.Address.City) for typed collections and dot-notation strings ("address.city") for schema-less collections. Null intermediates skipped.
• ✅ Projection Push-down: SELECT (and WHERE+SELECT) lambdas compile to a single-pass raw-BSON reader — T is never instantiated. IBLiteQueryable<T> preserves the async chain across all LINQ operators.
• ✅ BLQL: MQL-inspired query language for DynamicCollection — filter, sort, project and page BsonDocument results from JSON strings or via a fluent C# API. Full operator set: comparison, string ($startsWith, $endsWith, $contains), array ($elemMatch, $size, $all), arithmetic ($mod), logical, geospatial ($geoWithin, $geoNear), and vector ($nearVector). Security-hardened against injection, ReDoS, and division-by-zero.
• ✅ Native TimeSeries: Dedicated PageType.TimeSeries (12) with append-only layout, LastTimestamp header field and automatic retention-based pruning. Triggered on insert — no background threads. SetTimeSeries(), ForcePrune(), IsTimeSeries, GetTimeSeriesConfig() on DynamicCollection. Studio UI: TimeSeries tab, TS badge in sidebar.
• ✅ Page Compaction on Delete: Intra-page space is reclaimed on every delete — live documents are packed toward the top of the page, FreeSpaceEnd is updated and the free-space map is refreshed immediately. Deleted bytes are reusable without a VACUUM pass.
• ✅ Typed TimeSeries (DocumentDbContext): HasTimeSeries(x => x.Timestamp, retention) fluent API on EntityTypeBuilder<T>. Configure a typed DocumentDbContext collection as a TimeSeries source from OnModelCreating. ForcePrune() available on DocumentCollection<TId, T>.
• ✅ Auto ID Fallback for string and Guid (v3.4.0): primary keys of type string are auto-generated as CUID-style strings and Guid keys use Guid.NewGuid() — no manual ID assignment required on insert. Fixed index navigation for number-based indexes.
• ✅ IDocumentCollection<TId, T> Abstraction (v3.5.0): typed collections implement IDocumentCollection<TId, T> — a clean interface covering CRUD, LINQ, async, and bulk operations (Update, UpdateBulk, Delete, DeleteBulk). Enables constructor injection and mocking without coupling to the concrete DocumentCollection class.
• ✅ CDC Watch on DynamicCollection (v3.6.0): DynamicCollection.Watch() adds real-time change streams to the schema-less API — previously only available on typed DocumentCollection<TId, T>.
• ✅ HNSW Vector Search Correctness (v3.6.2): full correctness pass — fixes AllocateNode overflow, neighbor link integrity, SelectNeighbors heuristic, random level distribution (mL = 1/ln(M)), and index persistence across close/reopen. 12 dedicated edge-case tests added.

🔮 Future Vision

1. Advanced Querying & Specialized Indices

• Graph Traversals:
  • Specialized index for "links" (Document IDs) for $O(1)$ navigation without full scans.

2. CDC & Event Integration

• BSON Change Stream: "Log Miner" that decodes WAL entries and emits structured events.
• Internal Dispatcher: Keeps specialized indices updated automatically via CDC.

3. Performance & Optimization

• Portability: ✅ .netstandard2.1 support shipped in v2.0 — compatible with Unity, MAUI, Xamarin, and .NET 5+.

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🤝 Contributing

We welcome contributions! This is a great project to learn about database internals, B-Trees, and high-performance .NET.

How to Build

1. Clone: git clone https://github.com/mrdevrobot/BLite.git
2. Build: dotnet build
3. Test: dotnet test (We have comprehensive tests for Storage, Indexing, and LINQ).

Areas to Contribute

• Missing LINQ Operators: Help us implement additional IQueryable functions.
• Benchmarks: Help us prove BLite is faster than the competition.
• Documentation: Examples, Guides, and Wiki.

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📝 License

Licensed under the MIT License. Use it freely in personal and commercial projects.