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NoSQL & Document Store

MongoDB compatible document-oriented database engine. Store flexible JSON data structures, index your collections, and run complex aggregation pipelines.

9 min read·Level intermediate·Revised on Aug 19, 2026
This English text was generated automatically from the French original and has not been reviewed yet.
#
Overview

The Aurabase Document Store

In addition to the PostgreSQL relational engine, Aurabase allows you to activate a NoSQL Document Store engine isolated by project. It offers the flexibility of semi-structured documents with the robustness of the Aurabase infrastructure (backups, access control, observability).

Recommended use cases

Choose the NoSQL engine for tracking/analytics events, product catalogs with heterogeneous attributes, real-time telemetry and user sessions.

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Examples

Collection operations

nosql-insert.tstypescript
const { data, error } = await aura.nosql
  .collection('events')
  .insertOne({
    type: 'user_signup',
    userId: 'usr_9482',
    metadata: { country: 'FR', plan: 'pro' },
    timestamp: new Date(),
  })
#
Features

Engine optimized for production

Flexible scheme

Dynamic JSON/BSON documents. Ideal for logs, e-commerce catalogs, IoT telemetry and non-standardized profiles.

Query operators

$eq, $ne, $in, $nin, $gt, $gte, $regex, $exists and queries on nested objects and arrays.

Aggregation Pipelines

Multi-step transformations with $match, $project, $group, $sort, $unwind and streaming metric calculations.

Powerful indexing

Simple, compound, text indexes for full-text search and TTL indexes with automatic purge of expired documents.

Explain & Profiling

Detailed execution plan for each query (COLLSCAN vs IXSCAN, execution time, indexes used).

REST API & Unified SDK

Direct access via REST endpoints /v1/nosql/{project_id}/* or the @aurabase/aurabase-js SDK.

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Performance

Query Optimization (Explain)

Each query can be analyzed to inspect the execution steps, identify if an index was requested (IXSCAN) or if a full scan took place (COLLSCAN):

explain-plan.jsonjson
{
  "queryPlanner": {
    "winningPlan": {
      "stage": "IXSCAN",
      "indexName": "metadata.country_1_timestamp_-1",
      "keysExamined": 42,
      "docsExamined": 42
    },
    "executionTimeMillis": 1.2
  }
}
#
Architecture

PostgreSQL vs NoSQL: Which engine to choose?

CriterionPostgreSQL (Relational)Document Store (NoSQL)

StructureStrict schema, versioned migrationsDynamic schema without rigid constraints

Relations & JointuresComplex SQL joins, foreign keysNested / denormalized documents

Contrôle d’accèsRow-Level Security (RLS) declarative SQLPermissions by collection & role token

Recherche Vectoriellenative pgvector with HNSWFiltering by attributes and text indexes

Idéal pourCore banking, B2B SaaS, rights managementLogs, dynamic catalogs, IoT, events

Last updated · Aug 19, 2026