Composite Storage

MastraCompositeStore can compose storage domains from different providers. Use it when you need different databases for different purposes. For example, use LibSQL for memory and PostgreSQL for workflows.

Installation

MastraCompositeStore is included in @mastra/core:

npm

npm install @mastra/core@latest

pnpm

pnpm add @mastra/core@latest

Yarn

yarn add @mastra/core@latest

Bun

bun add @mastra/core@latest

You'll also need to install the storage providers you want to compose:

npm

npm install @mastra/pg@latest @mastra/libsql@latest

pnpm

pnpm add @mastra/pg@latest @mastra/libsql@latest

Yarn

yarn add @mastra/pg@latest @mastra/libsql@latest

Bun

bun add @mastra/pg@latest @mastra/libsql@latest

Storage domains

Mastra organizes storage into five specialized domains, each handling a specific type of data. Each domain can be backed by a different storage adapter, and domain classes are exported from each storage package.

Domain	Description
memory	Conversation persistence for agents. Stores threads (conversation sessions), messages, resources (user identities), and working memory (persistent context across conversations).
workflows	Workflow execution state. When workflows suspend for human input, external events, or scheduled resumption, their state is persisted here to enable resumption after server restarts.
scores	Evaluation results from Mastra's evals system. Scores and metrics are persisted here for analysis and comparison over time.
observability	Telemetry data including traces and spans. Agent interactions, tool calls, and LLM requests generate spans collected into traces for debugging and performance analysis.
agents	Agent configurations for stored agents. Enables agents to be defined and updated at runtime without code deployments.

Usage

Basic composition

Import domain classes directly from each store package and compose them:

src/mastra/index.ts

import { MastraCompositeStore } from "@mastra/core/storage";
import { WorkflowsPG, ScoresPG } from "@mastra/pg";
import { MemoryLibSQL } from "@mastra/libsql";
import { Mastra } from "@mastra/core";

export const mastra = new Mastra({
  storage: new MastraCompositeStore({
    id: "composite",
    domains: {
      memory: new MemoryLibSQL({ url: "file:./local.db" }),
      workflows: new WorkflowsPG({ connectionString: process.env.DATABASE_URL }),
      scores: new ScoresPG({ connectionString: process.env.DATABASE_URL }),
    },
  }),
});

With a default storage

Use default to specify a fallback storage, then override specific domains:

src/mastra/index.ts

import { MastraCompositeStore } from "@mastra/core/storage";
import { PostgresStore } from "@mastra/pg";
import { MemoryLibSQL } from "@mastra/libsql";
import { Mastra } from "@mastra/core";

const pgStore = new PostgresStore({
  id: "pg",
  connectionString: process.env.DATABASE_URL,
});

export const mastra = new Mastra({
  storage: new MastraCompositeStore({
    id: "composite",
    default: pgStore,
    domains: {
      memory: new MemoryLibSQL({ url: "file:./local.db" }),
    },
  }),
});

Options

id:

string

Unique identifier for this storage instance.

default?:

MastraCompositeStore

Default storage adapter. Domains not explicitly specified in `domains` will use this storage's domains as fallbacks.

domains?:

object

Individual domain overrides. Each domain can come from a different storage adapter. These take precedence over the default storage.

domains.memory?:

MemoryStorage

Storage for threads, messages, and resources.

domains.workflows?:

WorkflowsStorage

Storage for workflow snapshots.

domains.scores?:

ScoresStorage

Storage for evaluation scores.

domains.observability?:

ObservabilityStorage

Storage for traces and spans.

domains.agents?:

AgentsStorage

Storage for stored agent configurations.

disableInit?:

boolean

When true, automatic initialization is disabled. You must call init() explicitly.

Initialization

MastraCompositeStore initializes each configured domain independently. When passed to the Mastra class, init() is called automatically:

src/mastra/index.ts

import { MastraCompositeStore } from "@mastra/core/storage";
import { MemoryPG, WorkflowsPG, ScoresPG } from "@mastra/pg";
import { Mastra } from "@mastra/core";

const storage = new MastraCompositeStore({
  id: "composite",
  domains: {
    memory: new MemoryPG({ connectionString: process.env.DATABASE_URL }),
    workflows: new WorkflowsPG({ connectionString: process.env.DATABASE_URL }),
    scores: new ScoresPG({ connectionString: process.env.DATABASE_URL }),
  },
});

export const mastra = new Mastra({
  storage, // init() called automatically
});

If using storage directly, call init() explicitly:

import { MastraCompositeStore } from "@mastra/core/storage";
import { MemoryPG } from "@mastra/pg";

const storage = new MastraCompositeStore({
  id: "composite",
  domains: {
    memory: new MemoryPG({ connectionString: process.env.DATABASE_URL }),
  },
});

await storage.init();

// Access domain-specific stores via getStore()
const memoryStore = await storage.getStore("memory");
const thread = await memoryStore?.getThreadById({ threadId: "..." });

Use cases

Separate databases for different workloads

Use a local database for development while keeping production data in a managed service:

import { MastraCompositeStore } from "@mastra/core/storage";
import { MemoryPG, WorkflowsPG, ScoresPG } from "@mastra/pg";
import { MemoryLibSQL } from "@mastra/libsql";

const storage = new MastraCompositeStore({
  id: "composite",
  domains: {
    // Use local SQLite for development, PostgreSQL for production
    memory:
      process.env.NODE_ENV === "development"
        ? new MemoryLibSQL({ url: "file:./dev.db" })
        : new MemoryPG({ connectionString: process.env.DATABASE_URL }),
    workflows: new WorkflowsPG({ connectionString: process.env.DATABASE_URL }),
    scores: new ScoresPG({ connectionString: process.env.DATABASE_URL }),
  },
});

Specialized storage for observability

Observability data can quickly overwhelm general-purpose databases in production. A single agent interaction can generate hundreds of spans, and high-traffic applications can produce thousands of traces per day.

ClickHouse is recommended for production observability because it's optimized for high-volume, write-heavy analytics workloads. Use composite storage to route observability to ClickHouse while keeping other data in your primary database:

import { MastraCompositeStore } from "@mastra/core/storage";
import { MemoryPG, WorkflowsPG, ScoresPG } from "@mastra/pg";
import { ObservabilityStorageClickhouse } from "@mastra/clickhouse";

const storage = new MastraCompositeStore({
  id: "composite",
  domains: {
    memory: new MemoryPG({ connectionString: process.env.DATABASE_URL }),
    workflows: new WorkflowsPG({ connectionString: process.env.DATABASE_URL }),
    scores: new ScoresPG({ connectionString: process.env.DATABASE_URL }),
    observability: new ObservabilityStorageClickhouse({
      url: process.env.CLICKHOUSE_URL,
      username: process.env.CLICKHOUSE_USERNAME,
      password: process.env.CLICKHOUSE_PASSWORD,
    }),
  },
});

info

This approach is also required when using storage providers that don't support observability (like Convex, DynamoDB, or Cloudflare). See the DefaultExporter documentation for the full list of supported providers.