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Build Custom Stores and Destinations

30 minutes: Implement your own stores and destinations.

Prerequisites: Completed Your First Pipeline or familiar with ETL basics.

Understanding the Destination Trait

ETL delivers data to destinations in two phases:

Phase Method When Data Type
Initial Copy write_table_rows() Startup Vec<TableRow>
Streaming write_events() After copy Vec<Event>

Note: During initial copy, parallel table sync workers each process their own replication slot, so Begin and Commit transaction markers may appear multiple times. This does not duplicate actual row data.

Step 1: Create the Project

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cargo new etl-custom --lib
cd etl-custom

Update Cargo.toml:

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[package]
name = "etl-custom"
version = "0.1.0"
edition = "2021"

[[bin]]
name = "main"
path = "src/main.rs"

[dependencies]
etl = { git = "https://github.com/supabase/etl" }
tokio = { version = "1.0", features = ["full"] }
reqwest = { version = "0.11", features = ["json"] }
serde_json = "1.0"
tracing = "0.1"
tracing-subscriber = "0.3"

Verify: cargo check succeeds.

Step 2: Implement a Custom Store

Create src/custom_store.rs. A store must implement three traits (see Extension Points for full details):

  • SchemaStore - Table schema storage and retrieval
  • StateStore - Replication progress and table mapping tracking
  • CleanupStore - Metadata cleanup when tables leave the publication
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use std::collections::HashMap;
use std::sync::Arc;
use tokio::sync::Mutex;
use tracing::info;

use etl::error::EtlResult;
use etl::state::table::TableReplicationPhase;
use etl::store::cleanup::CleanupStore;
use etl::store::schema::SchemaStore;
use etl::store::state::StateStore;
use etl::types::{TableId, TableSchema};

#[derive(Debug, Clone, Default)]
struct TableEntry {
    schema: Option<Arc<TableSchema>>,
    state: Option<TableReplicationPhase>,
    mapping: Option<String>,
}

#[derive(Debug, Clone)]
pub struct CustomStore {
    tables: Arc<Mutex<HashMap<TableId, TableEntry>>>,
}

impl CustomStore {
    pub fn new() -> Self {
        info!("creating custom store");
        Self {
            tables: Arc::new(Mutex::new(HashMap::new())),
        }
    }
}

impl SchemaStore for CustomStore {
    async fn get_table_schema(&self, table_id: &TableId) -> EtlResult<Option<Arc<TableSchema>>> {
        let tables = self.tables.lock().await;
        Ok(tables.get(table_id).and_then(|e| e.schema.clone()))
    }

    async fn get_table_schemas(&self) -> EtlResult<Vec<Arc<TableSchema>>> {
        let tables = self.tables.lock().await;
        Ok(tables.values().filter_map(|e| e.schema.clone()).collect())
    }

    async fn load_table_schemas(&self) -> EtlResult<usize> {
        Ok(0) // In-memory store, nothing to load
    }

    async fn store_table_schema(&self, schema: TableSchema) -> EtlResult<()> {
        let mut tables = self.tables.lock().await;
        let id = schema.id;
        tables.entry(id).or_default().schema = Some(Arc::new(schema));
        Ok(())
    }
}

impl StateStore for CustomStore {
    async fn get_table_replication_state(
        &self,
        table_id: TableId,
    ) -> EtlResult<Option<TableReplicationPhase>> {
        let tables = self.tables.lock().await;
        Ok(tables.get(&table_id).and_then(|e| e.state.clone()))
    }

    async fn get_table_replication_states(
        &self,
    ) -> EtlResult<HashMap<TableId, TableReplicationPhase>> {
        let tables = self.tables.lock().await;
        Ok(tables
            .iter()
            .filter_map(|(id, e)| e.state.clone().map(|s| (*id, s)))
            .collect())
    }

    async fn load_table_replication_states(&self) -> EtlResult<usize> {
        Ok(0)
    }

    async fn update_table_replication_state(
        &self,
        table_id: TableId,
        state: TableReplicationPhase,
    ) -> EtlResult<()> {
        info!("table {} -> {:?}", table_id.0, state);
        let mut tables = self.tables.lock().await;
        tables.entry(table_id).or_default().state = Some(state);
        Ok(())
    }

    async fn rollback_table_replication_state(
        &self,
        _table_id: TableId,
    ) -> EtlResult<TableReplicationPhase> {
        todo!("Implement rollback if needed")
    }

    async fn get_table_mapping(&self, table_id: &TableId) -> EtlResult<Option<String>> {
        let tables = self.tables.lock().await;
        Ok(tables.get(table_id).and_then(|e| e.mapping.clone()))
    }

    async fn get_table_mappings(&self) -> EtlResult<HashMap<TableId, String>> {
        let tables = self.tables.lock().await;
        Ok(tables
            .iter()
            .filter_map(|(id, e)| e.mapping.clone().map(|m| (*id, m)))
            .collect())
    }

    async fn load_table_mappings(&self) -> EtlResult<usize> {
        Ok(0)
    }

    async fn store_table_mapping(
        &self,
        table_id: TableId,
        mapping: String,
    ) -> EtlResult<()> {
        let mut tables = self.tables.lock().await;
        tables.entry(table_id).or_default().mapping = Some(mapping);
        Ok(())
    }
}

impl CleanupStore for CustomStore {
    async fn cleanup_table_state(&self, table_id: TableId) -> EtlResult<()> {
        let mut tables = self.tables.lock().await;
        tables.remove(&table_id);
        Ok(())
    }
}

Verify: cargo check succeeds.

Step 3: Implement a Custom Destination

Create src/http_destination.rs. A destination implements the Destination trait with four required methods:

  • name() - Return an identifier for logging
  • truncate_table() - Clear table before bulk load (called even if table does not exist)
  • write_table_rows() - Receive rows during initial copy (may receive empty vec for table creation)
  • write_events() - Receive streaming changes (batches may span multiple tables)

There's also an optional shutdown() method with a default no-op implementation. Override it if your destination needs cleanup when the pipeline shuts down.

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use reqwest::Client;
use serde_json::json;
use std::time::Duration;
use tracing::{info, warn};

use etl::destination::Destination;
use etl::error::{ErrorKind, EtlResult};
use etl::types::{Event, TableId, TableRow};
use etl::{bail, etl_error};

#[derive(Debug, Clone)]
pub struct HttpDestination {
    client: Client,
    base_url: String,
}

impl HttpDestination {
    pub fn new(base_url: String) -> EtlResult<Self> {
        let client = Client::builder()
            .timeout(Duration::from_secs(30))
            .build()
            .map_err(|e| etl_error!(ErrorKind::Unknown, "HTTP client error", source: e))?;
        Ok(Self { client, base_url })
    }

    async fn post(&self, path: &str, body: serde_json::Value) -> EtlResult<()> {
        let url = format!("{}/{}", self.base_url.trim_end_matches('/'), path);

        for attempt in 1..=3 {
            match self.client.post(&url).json(&body).send().await {
                Ok(resp) if resp.status().is_success() => return Ok(()),
                Ok(resp) if resp.status().is_client_error() => {
                    bail!(ErrorKind::Unknown, "Client error", resp.status());
                }
                Ok(resp) => warn!("attempt {}/3: status {}", attempt, resp.status()),
                Err(e) => warn!("attempt {}/3: {}", attempt, e),
            }
            if attempt < 3 {
                tokio::time::sleep(Duration::from_millis(500 * attempt as u64)).await;
            }
        }
        bail!(ErrorKind::Unknown, "Request failed after retries");
    }
}

impl Destination for HttpDestination {
    fn name() -> &'static str {
        "http"
    }

    async fn truncate_table(
        &self,
        table_id: TableId,
        async_result: TruncateTableResult<()>,
    ) -> EtlResult<()> {
        info!("truncating table {}", table_id.0);
        let result = self.post(&format!("tables/{}/truncate", table_id.0), json!({})).await;
        async_result.send(result);
        Ok(())
    }

    async fn write_table_rows(
        &self,
        table_id: TableId,
        rows: Vec<TableRow>,
        async_result: WriteTableRowsResult<()>,
    ) -> EtlResult<()> {
        if rows.is_empty() {
            async_result.send(Ok(()));
            return Ok(());
        }
        info!("writing {} rows to table {}", rows.len(), table_id.0);

        let payload = json!({
            "table_id": table_id.0,
            "rows": rows.iter().map(|r| {
                json!({ "values": r.values.iter().map(|v| format!("{:?}", v)).collect::<Vec<_>>() })
            }).collect::<Vec<_>>()
        });

        let result = self.post(&format!("tables/{}/rows", table_id.0), payload).await;
        async_result.send(result);
        Ok(())
    }

    async fn write_events(
        &self,
        events: Vec<Event>,
        async_result: WriteEventsResult<()>,
    ) -> EtlResult<()> {
        if events.is_empty() {
            async_result.send(Ok(()));
            return Ok(());
        }
        info!("writing {} events", events.len());

        let payload = json!({
            "events": events.iter().map(|e| {
                match e {
                    Event::Insert(i) => json!({"type": "insert", "table": i.table_id.0}),
                    Event::Update(u) => json!({"type": "update", "table": u.table_id.0}),
                    Event::Delete(d) => json!({"type": "delete", "table": d.table_id.0}),
                    Event::Begin(_) => json!({"type": "begin"}),
                    Event::Commit(_) => json!({"type": "commit"}),
                    Event::Relation(r) => json!({"type": "relation", "table": r.table_schema.id.0}),
                    Event::Truncate(t) => json!({"type": "truncate", "tables": t.rel_ids}),
                    Event::Unsupported => json!({"type": "unsupported"}),
                }
            }).collect::<Vec<_>>()
        });

        let result = self.post("events", payload).await;
        async_result.send(result);
        Ok(())
    }
}

Verify: cargo check succeeds.

Step 4: Wire It Together

Create src/main.rs:

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mod custom_store;
mod http_destination;

use custom_store::CustomStore;
use etl::config::{BatchConfig, PgConnectionConfig, PipelineConfig, TlsConfig};
use etl::pipeline::Pipeline;
use http_destination::HttpDestination;
use std::error::Error;

#[tokio::main]
async fn main() -> Result<(), Box<dyn Error>> {
    tracing_subscriber::fmt::init();

    let store = CustomStore::new();
    let destination = HttpDestination::new("https://your-endpoint.example.com".to_string())?;

    let config = PipelineConfig {
        id: 1,
        publication_name: "my_publication".to_string(),
        pg_connection: PgConnectionConfig {
            host: "localhost".to_string(),
            port: 5432,
            name: "your_database".to_string(),
            username: "postgres".to_string(),
            password: Some("your_password".to_string().into()),
            tls: TlsConfig {
                enabled: false,
                trusted_root_certs: String::new(),
            },
            keepalive: None,
        },
        batch: BatchConfig {
            max_size: 1000,
            max_fill_ms: 5000,
        },
        table_error_retry_delay_ms: 10000,
        table_error_retry_max_attempts: 5,
        max_table_sync_workers: 4,
    };

    println!("Starting pipeline...");
    let mut pipeline = Pipeline::new(config, store, destination);
    pipeline.start().await?;
    pipeline.wait().await?;

    Ok(())
}

Note: Update the database name, password, and HTTP endpoint to match your setup.

Step 5: Test

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cargo run

The pipeline will connect to Postgres and start replicating. You'll see your custom store logging state transitions and your destination receiving HTTP calls.

What You Built

  • Custom Store - In-memory implementation of SchemaStore, StateStore, and CleanupStore
  • HTTP Destination - Forwards replicated data via HTTP POST with retry logic
  • Working Pipeline - Connects your custom components to the ETL core

Next Steps