# PostgreSQL Database Extractor (`parseforge/postgresql-database-extractor`) Actor Extract an entire PostgreSQL database into Apify storage using a connection string or individual parameters. Supports table filtering, flexible output formats, and automated export of all rows and metadata for seamless integration with other Actors or workflows. - **URL**: https://apify.com/parseforge/postgresql-database-extractor.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Automation, Other, Developer tools - **Stats:** 3 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## πŸ’Ύ PostgreSQL Database Extractor > πŸ•’ **Last updated:** 2026-05-05 Extract your entire PostgreSQL database without coding. Whether you need to back up critical data, migrate to a new system, or analyze tables for compliance, this tool exports all tables with complete flexibility. Connect via a single string or individual parameters, filter which tables to include, and get your data as JSON, CSV, or Excel. No setup required, no database knowledge needed. > **The PostgreSQL Database Extractor collects all your database tables as structured datasets. Extract unlimited columns and rows per table with no coding required.** ### ✨ What Does It Do - πŸ“Š **Table List** - Discover all available tables in your database with row and column counts to plan your extraction - πŸ“„ **Table Data** - Export complete row data from each table with all column types preserved for downstream analysis - πŸ“… **Extraction Timestamp** - Track when each table was extracted for audit trails and data freshness verification - πŸ”’ **Row Count** - Get accurate counts of rows per table to estimate export size and validate completeness - πŸ—οΈ **Schema Information** - Understand table structure with column names, data types, and positions for ETL pipelines - πŸ”— **Dataset URLs** - Access pre-generated links to your extracted data for easy sharing and documentation ### πŸ”§ Input - **Connection String (Optional)** - Paste your full PostgreSQL connection string (e.g., postgresql://user:password@host:port/database) to skip individual parameters - **Host** - The IP address or hostname of your PostgreSQL server (e.g., db.example.com or 192.168.1.1) - **Port** - The port PostgreSQL listens on, typically 5432 - **Database** - The name of the database to connect to - **Username** - Your PostgreSQL user account with appropriate table access permissions - **Password** - Your PostgreSQL password for secure authentication - **Use SSL** - Enable encrypted connection for cloud databases (required by most managed services) - **Tables to Extract (Optional)** - Specify exact table names to extract only those (e.g., ['public.users', 'public.orders']). Leave empty to extract all - **Tables to Exclude (Optional)** - Blacklist specific tables you don't need (e.g., ['public.logs', 'public.temp_data']) - **Max Rows Per Table (Optional)** - Limit the number of rows extracted from each table for faster processing Example input: ```json { "host": "db.example.com", "port": 5432, "database": "production", "username": "extractor_user", "password": "your-secure-password", "ssl": true, "tables": ["public.customers", "public.orders"], "maxRowsPerTable": 50000 } ```` ### πŸ“Š Output Each database extraction includes table metadata and row data. Download as JSON, CSV, or Excel. | πŸ“‹ Table Name | πŸ“Š Row Count | πŸ—οΈ Schema Name | |---|---|---| | πŸ”’ Column Count | πŸ“ Column Names | πŸ”„ Column Data Types | | πŸ“… Extraction Date | πŸ†” Column Positions | πŸ”— Dataset URL | ### πŸ’Ž Why Choose the PostgreSQL Database Extractor? | Feature | Our Actor | Similar Tools | |---|---|---| | No coding required | βœ”οΈ | ❌ | | Connection string or individual parameters | βœ”οΈ | Partial | | Filter by specific tables | βœ”οΈ | ❌ | | Exclude tables by name | βœ”οΈ | ❌ | | Row limits per table | βœ”οΈ | ❌ | | Batch processing for memory efficiency | βœ”οΈ | ❌ | | Real-time extraction timestamps | βœ”οΈ | ❌ | | Separate datasets per table | βœ”οΈ | ❌ | | Column metadata and types included | βœ”οΈ | Partial | | Free tier with $5 credit | βœ”οΈ | ❌ | | Handles large databases efficiently | βœ”οΈ | Partial | | CSV, JSON, and Excel export | βœ”οΈ | βœ”οΈ | ### πŸ“‹ How to Use No technical skills required. Follow these simple steps: 1. **Sign Up**: [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) 2. **Find the Tool**: Search for "PostgreSQL Database Extractor" in the Apify Store and configure your database connection details 3. **Run It**: Click "Start" and watch your tables extract into datasets That's it. No coding, no setup, no complicated configuration. Export your data in CSV, Excel, or JSON format. ### 🎯 Business Use Cases - πŸ“Š **Data Analyst** - Extract sales tables weekly to track revenue trends and customer growth in your BI platform - πŸ’Ό **Database Administrator** - Backup production tables for disaster recovery and maintain historical extracts for compliance - πŸ”¬ **Data Engineer** - Export database tables to cloud storage and feed them into your ETL pipeline *** *** ### ✨ Why choose this Actor | | Capability | |---|---| | 🎯 | **Built for the job.** Scoped specifically to this data source so you skip the parser engineering entirely. | | πŸ”– | **Structured output.** Clean, typed fields ready for analysis, dashboards, or downstream pipelines. | | ⚑ | **Fast.** Optimized request patterns return results in seconds, not minutes. | | πŸ” | **Always fresh.** Every run pulls live data, so the dataset reflects the source as of run time. | | 🌐 | **No infra to manage.** Apify handles proxies, retries, scaling, scheduling, and storage. | | πŸ›‘οΈ | **Reliable.** Battle-tested across many runs and edge cases, with graceful error handling. | | 🚫 | **No code required.** Configure in the UI, run from CLI, schedule via cron, or call from any language with the Apify SDK. | > πŸ“Š Production-grade structured data without the engineering overhead of building and maintaining your own scraper. *** ### πŸ“ˆ How it compares to alternatives | Approach | Cost | Coverage | Refresh | Filters | Setup | |---|---|---|---|---|---| | **⭐ PostgreSQL Database Extractor** *(this Actor)* | $5 free credit, then pay-per-use | Full source coverage | **Live per run** | Source-native filters supported | ⚑ 2 min | | Build your own scraper | Engineering hours | Full once built | Whenever you maintain it | Custom code | 🐒 Days to weeks | | Paid managed APIs | $$$ monthly | Vendor-defined | Live | Vendor-defined | ⏳ Hours | | Third-party data dumps | Varies | Subset, often stale | Periodic | None | πŸ•’ Variable | Pick this Actor when you want broad coverage, server-side filtering, and no pipeline maintenance. *** ### πŸš€ How to use 1. πŸ“ **Sign up.** [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) (takes 2 minutes). 2. 🌐 **Open the Actor.** Go to the PostgreSQL Database Extractor page on the Apify Store. 3. 🎯 **Set input.** Configure the input fields in the form (or paste a JSON), then set maxItems. 4. πŸš€ **Run it.** Click **Start** and let the Actor collect your data. 5. πŸ“₯ **Download.** Grab your results in the **Dataset** tab as CSV, Excel, JSON, or XML. > ⏱️ Total time from signup to downloaded dataset: **3-5 minutes.** No coding required. *** ### πŸ’Ό Business use cases
#### πŸ“Š Data & Analytics - Build trend reports and dashboards from live source data - Feed BI tools, warehouses, and ML pipelines with structured records - Run periodic snapshots to track changes over time - Compare segments, regions, or categories with consistent fields #### 🏒 Operations & Strategy - Monitor competitor moves, pricing, and inventory shifts - Build internal directories and lookup tools backed by current data - Power workflows that depend on fresh source records - Cut manual data-gathering time from hours to minutes
#### 🎯 Marketing & Growth - Identify market opportunities and trending topics - Research target audiences and customer personas at scale - Power lead-generation pipelines with verified records - Track sentiment, reviews, or social signals over time #### πŸ› οΈ Engineering & Product - Prototype features that need real-world data without owning a crawler - Replace fragile in-house scrapers with a managed Actor - Wire datasets into your apps via the Apify API or webhooks - Skip the proxy, retry, and parsing maintenance entirely
*** ### 🌟 Beyond business use cases Data like this powers more than commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.
#### πŸŽ“ Research and academia - Empirical datasets for papers, thesis work, and coursework - Longitudinal studies tracking changes across snapshots - Reproducible research with cited, versioned data pulls - Classroom exercises on data analysis and ethical scraping #### 🎨 Personal and creative - Side projects, portfolio demos, and indie app launches - Data visualizations, dashboards, and infographics - Content research for bloggers, YouTubers, and podcasters - Hobbyist collections and personal trackers
#### 🀝 Non-profit and civic - Transparency reporting and accountability projects - Advocacy campaigns backed by public-interest data - Community-run databases for local issues - Investigative journalism on public records #### πŸ§ͺ Experimentation - Prototype AI and machine-learning pipelines with real data - Validate product-market hypotheses before engineering spend - Train small domain-specific models on niche corpora - Test dashboard concepts with live input
### πŸ€– Ask an AI assistant about this scraper Open a ready-to-send prompt about this ParseForge actor in the AI of your choice: - πŸ’¬ [**ChatGPT**](https://chat.openai.com/?q=How%20do%20I%20use%20the%20PostgreSQL%20Database%20Extractor%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - 🧠 [**Claude**](https://claude.ai/new?q=How%20do%20I%20use%20the%20PostgreSQL%20Database%20Extractor%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - πŸ” [**Perplexity**](https://perplexity.ai/search?q=How%20do%20I%20use%20the%20PostgreSQL%20Database%20Extractor%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - πŸ…’ [**Copilot**](https://copilot.microsoft.com/?q=How%20do%20I%20use%20the%20PostgreSQL%20Database%20Extractor%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) ### πŸ’° How much does it cost? Apify gives you **$5 in free monthly credits** on the [Apify Free plan](https://apify.com/pricing), enough to test PostgreSQL Database Extractor and pull a real sample dataset. For ongoing usage: - **Starter plan ($49/month)** β€” Recommended for individuals running PostgreSQL Database Extractor regularly. Includes higher concurrency and larger datasets. - **Scale plan ($499/month)** β€” Recommended for teams running PostgreSQL Database Extractor at production scale. Pay-Per-Event pricing means you only pay for what you actually use. Failed runs are never charged. See the **Pricing** tab on this Actor's page for exact event prices. ### πŸ’‘ Tips for using PostgreSQL Database Extractor - **Start with a small maxItems** (3-10) to validate output format before running larger jobs. - **Use Apify Schedules** to run PostgreSQL Database Extractor on a recurring basis and keep your dataset fresh. - **Export via Integrations**: Apify connects to Google Sheets, Airbyte, Make, Zapier, and direct webhooks β€” pipe your data anywhere. - **Monitor with webhooks**: trigger downstream workflows the moment a run finishes. - **Re-run failed items**: if any individual records error out, re-run with their inputs only. Failed events are not charged. ### βš–οΈ Is it legal to use PostgreSQL Database Extractor? Yes. PostgreSQL Database Extractor only collects publicly available data. Web scraping public data has been confirmed as legal by US courts (see [hiQ Labs v. LinkedIn](https://en.wikipedia.org/wiki/HiQ_Labs_v._LinkedIn)) and is widely used for research, market analysis, and business intelligence. However, you are responsible for: - Respecting the source website's Terms of Service. - Complying with GDPR, CCPA, and other applicable data-protection laws when personal data is involved. - Not republishing copyrighted content without permission. If you have specific compliance concerns, consult your legal team. See the [Apify legal docs](https://docs.apify.com/legal) for more. ### ❓ Frequently Asked Questions
πŸ’³ Do I need a paid Apify plan to run this actor? No. You can start right now on the free Apify plan, which includes **$5 in free monthly credit**. That is enough to run this actor several times and explore the output before committing to anything. Paid plans unlock higher limits, more concurrent runs, and larger datasets. [Create a free Apify account here](https://console.apify.com/sign-up?fpr=vmoqkp) to get started.
🚨 What happens if my run fails or returns no results? Failed runs are not charged. If the source site changes, proxies get rate-limited, or a specific input matches nothing, re-run the actor or open our [contact form](https://tally.so/r/BzdKgA) and we will investigate. You can also check the run log in the Apify console to see why the run stopped.
πŸ“ How many items can I scrape per run? Free users are limited to **10 items per run** so you can preview the output and confirm the actor works for your use case. Paid users can raise maxItems up to **1,000,000** per run. [Upgrade here](https://console.apify.com/sign-up?fpr=vmoqkp) if you need full scale.
πŸ•’ How fresh is the data? Every run fetches live data at the moment of execution. There is no cache or delay: the records you get reflect what the source returned at that moment. Schedule the actor to maintain a rolling snapshot of the data you need.
πŸ§‘β€πŸ’» Can I call this actor from my own code? Yes. Apify exposes every actor as a REST endpoint and ships first-class SDKs for [Node.js](https://docs.apify.com/sdk/js) and [Python](https://docs.apify.com/sdk/python). You can start a run, read the dataset, and handle webhooks from your own app in a few lines. All you need is your Apify API token.
πŸ“€ How do I export the data? Every Apify dataset can be downloaded in one click from the console as CSV, JSON, JSONL, Excel, HTML, XML, or RSS. You can also pull results programmatically via the [Apify API](https://docs.apify.com/api/v2) or stream them into BigQuery, S3, and other destinations through built-in integrations.
πŸ“… Can I schedule the actor to run automatically? Yes. Use the Apify scheduler to run the actor on any cadence, from hourly to monthly. Results are saved to your dataset and can be delivered to webhooks, email, Slack, cloud storage, or automation tools such as Zapier and Make. ***
### πŸ”Œ Integrate with any app PostgreSQL Database Extractor connects to any cloud service via [Apify integrations](https://apify.com/integrations): - [**Make**](https://docs.apify.com/platform/integrations/make) - Automate multi-step workflows - [**Zapier**](https://docs.apify.com/platform/integrations/zapier) - Connect with 5,000+ apps - [**Slack**](https://docs.apify.com/platform/integrations/slack) - Get run notifications in your channels - [**Airbyte**](https://docs.apify.com/platform/integrations/airbyte) - Pipe results into your warehouse - [**GitHub**](https://docs.apify.com/platform/integrations/github) - Trigger runs from commits and releases - [**Google Drive**](https://docs.apify.com/platform/integrations/drive) - Export datasets straight to Sheets You can also use webhooks to trigger downstream actions when a run finishes. Push fresh data into your product backend, or alert your team in Slack. *** ### πŸ’‘ More ParseForge Actors - [MySQL Database Extractor](https://apify.com/parseforge/mysql-database-extractor) - Extract tables and data from MySQL databases - [Justia Case Law Scraper](https://apify.com/parseforge/justia-case-law-scraper) - Collect legal cases and court decisions - [NY Business Registry Scraper](https://apify.com/parseforge/apps-scraper) - Extract business entity data from state registries Browse our complete collection of [data extraction tools](https://apify.com/parseforge) for more. ### πŸš€ Ready to Start? [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) and extract your first 100 rows per table for free. No coding, no setup. ### πŸ†˜ Need Help? - Check the FAQ section above for common questions - Visit the [Apify support page](https://docs.apify.com) for documentation and tutorials - Contact us to request a new scraper, propose a custom project, or report an issue at [Tally contact form](https://tally.so/r/BzdKgA) ### ⚠️ Disclaimer > This Actor is an independent tool provided as-is. Users are responsible for complying with applicable laws and terms of service when processing data. All trademarks mentioned are the property of their respective owners. *** ### πŸ”— Recommended Actors - [**πŸ” Google Search Scraper**](https://apify.com/parseforge/google-search-scraper) - Multi-engine SERP results with country and language targeting - [**πŸ—ΊοΈ Nominatim OSM Scraper**](https://apify.com/parseforge/nominatim-osm-scraper) - Geocode addresses via OpenStreetMap - [**πŸ“Š Indexmundi Scraper**](https://apify.com/parseforge/indexmundi-scraper) - Global demographic and economic indicators - [**πŸ“° RAG Web Browser**](https://apify.com/parseforge/rag-web-browser) - Crawl and extract clean text from any URL for AI retrieval - [**🌐 Website Content Crawler**](https://apify.com/parseforge/website-content-crawler) - Crawl entire sites and export structured content > πŸ’‘ **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for more reference-data scrapers. # Actor input Schema ## `connectionString` (type: `string`): PostgreSQL connection string (e.g., postgresql://user:password@host:port/database). If provided, other connection parameters will be ignored. ## `host` (type: `string`): PostgreSQL server hostname or IP address ## `port` (type: `integer`): PostgreSQL server port (default: 5432) ## `database` (type: `string`): Database name to connect to ## `username` (type: `string`): PostgreSQL username ## `password` (type: `string`): PostgreSQL password ## `ssl` (type: `boolean`): Enable SSL connection (required for most cloud databases) ## `tables` (type: `array`): List of specific tables to extract (e.g., \['public.users', 'public.orders']). If not provided, all tables will be extracted. ## `excludeTables` (type: `array`): List of tables to exclude from extraction (e.g., \['public.logs', 'public.temp\_data']) ## `maxRowsPerTable` (type: `integer`): Maximum number of rows to extract from each table. If not specified, all rows will be extracted. ## Actor input object example ```json { "host": "localhost", "port": 5432, "database": "mydb", "username": "user", "password": "password", "tables": [], "excludeTables": [], "maxRowsPerTable": 100 } ``` # Actor output Schema ## `overview` (type: `string`): Overview view of tables with key fields displayed in a table format ## `tables` (type: `string`): Complete table dataset with all fields including table name, column information, extraction metadata, and dataset URLs # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "host": "localhost", "port": 5432, "database": "mydb", "username": "user", "password": "password", "tables": [], "excludeTables": [], "maxRowsPerTable": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/postgresql-database-extractor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "host": "localhost", "port": 5432, "database": "mydb", "username": "user", "password": "password", "tables": [], "excludeTables": [], "maxRowsPerTable": 100, } # Run the Actor and wait for it to finish run = client.actor("parseforge/postgresql-database-extractor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "host": "localhost", "port": 5432, "database": "mydb", "username": "user", "password": "password", "tables": [], "excludeTables": [], "maxRowsPerTable": 100 }' | apify call parseforge/postgresql-database-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/postgresql-database-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "PostgreSQL Database Extractor", "description": "Extract an entire PostgreSQL database into Apify storage using a connection string or individual parameters. Supports table filtering, flexible output formats, and automated export of all rows and metadata for seamless integration with other Actors or workflows.", "version": "1.0", "x-build-id": "TFX8EMfEwTD8Lgwrk" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~postgresql-database-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-postgresql-database-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~postgresql-database-extractor/runs": { "post": { "operationId": "runs-sync-parseforge-postgresql-database-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~postgresql-database-extractor/run-sync": { "post": { "operationId": "run-sync-parseforge-postgresql-database-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "host", "port", "database", "username", "password" ], "properties": { "connectionString": { "title": "Connection String (Optional)", "type": "string", "description": "PostgreSQL connection string (e.g., postgresql://user:password@host:port/database). If provided, other connection parameters will be ignored." }, "host": { "title": "Host", "type": "string", "description": "PostgreSQL server hostname or IP address" }, "port": { "title": "Port", "minimum": 1, "maximum": 65535, "type": "integer", "description": "PostgreSQL server port (default: 5432)" }, "database": { "title": "Database", "type": "string", "description": "Database name to connect to" }, "username": { "title": "Username", "type": "string", "description": "PostgreSQL username" }, "password": { "title": "Password", "type": "string", "description": "PostgreSQL password" }, "ssl": { "title": "Use SSL", "type": "boolean", "description": "Enable SSL connection (required for most cloud databases)" }, "tables": { "title": "Tables to Extract (Optional)", "type": "array", "description": "List of specific tables to extract (e.g., ['public.users', 'public.orders']). If not provided, all tables will be extracted.", "items": { "type": "string" } }, "excludeTables": { "title": "Tables to Exclude (Optional)", "type": "array", "description": "List of tables to exclude from extraction (e.g., ['public.logs', 'public.temp_data'])", "items": { "type": "string" } }, "maxRowsPerTable": { "title": "Max Rows Per Table (Optional)", "minimum": 1, "type": "integer", "description": "Maximum number of rows to extract from each table. If not specified, all rows will be extracted." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```