Software Alternatives, Accelerators & Startups

socketify.py VS DataPortia

Compare socketify.py VS DataPortia and see what are their differences

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socketify.py logo socketify.py

Maybe the fastest web framework for Python and PyPy

DataPortia logo DataPortia

DataPortia is an industrial data acquisition software that connects to any OPC UA automation system. Collect, visualize, and analyze your process data in real time โ€” with on-premises AI powered by local LLMs.
  • socketify.py Landing page
    Landing page //
    2023-09-24
  • DataPortia DataPortia customizable dashboard with gauge value chart bar and table widgets
    DataPortia customizable dashboard with gauge value chart bar and table widgets //
    2026-03-11
  • DataPortia DataPortia tabular report with aggregated industrial data and CSV PDF export options
    DataPortia tabular report with aggregated industrial data and CSV PDF export options //
    2026-03-11
  • DataPortia DataPortia interactive trend charts showing historical OPC UA process data visualization
    DataPortia interactive trend charts showing historical OPC UA process data visualization //
    2026-03-11
  • DataPortia DataPortia AI analysis wizard with anomaly detection and local LLM powered insights
    DataPortia AI analysis wizard with anomaly detection and local LLM powered insights //
    2026-03-11
  • DataPortia DataPortia OPC UA tag configuration with blocks categories and multilingual comments
    DataPortia OPC UA tag configuration with blocks categories and multilingual comments //
    2026-03-11
  • DataPortia DataPortia AI chat interface for natural language industrial data analysis
    DataPortia AI chat interface for natural language industrial data analysis //
    2026-03-11

DataPortia is an advanced industrial data acquisition and reporting software that connects to automation systems via OPC UA protocol. It stores time-series data in a PostgreSQL/TimescaleDB database and provides a web-based interface for real-time monitoring, trend analysis, and report generation.

Key Features: - Efficient data acquisition from automation systems via OPC UA protocol - Support for multiple simultaneous OPC UA connections with redundancy - Real-time dashboard with gauges, charts, bar charts, and tables - Interactive trend views with ECharts visualization and color customization - Comprehensive reporting with CSV and PDF export - Automated report scheduling (daily, weekly, monthly, custom) - AI-powered data analysis with local Ollama LLM (anomalies, forecasts, reports) - OPC UA Alarms & Conditions management with analytics and export - OPC UA history read from server historian - Calculation circuits (cumulative and non-cumulative formulas) - Tag transfer, copy and merge between connections - TimescaleDB time-series database with efficient compression and retention - Continuous aggregates (minute, hourly, daily, weekly) for fast queries - Automatic database backup and restore with scheduling - User management with role-based permissions (local or Azure AD) - Licensing: perpetual, trial, and floating licenses - Automatic HTTPS certificate management - API interface for third-party systems - Web interface for all devices (Finnish/English/Swedish/German)

System Requirements: - Windows 10/11 or Windows Server 2016+ (or Linux) - PostgreSQL 18 + TimescaleDB extension (included in setup) - Minimum 8 GB RAM (16 GB+ recommended) - Minimum 100 GB disk space (depending on data volume)

socketify.py

Website
github.com
Pricing URL
-
$ Details
-
Platforms
-
Release Date
-

DataPortia

Website
atorcom.fi
$ Details
paid Free Trial โ‚ฌ4,000 / One-off (Price scales by number of OPC UA connections)
Platforms
Windows Linux
Release Date
2025 January
Startup details
Country
Finland
City
Karstula
Founder(s)
Antti Haaraniemi
Employees
1 - 9

socketify.py features and specs

  • High Performance
    Socketify.py is designed for high scalability and performance, leveraging an efficient event loop and native extensions to handle a large number of concurrent connections efficiently.
  • WebSocket Support
    The library provides built-in support for WebSockets, making it suitable for real-time applications where persistent connections between client and server are necessary.
  • Asynchronous I/O
    Socketify.py is built on top of asynchronous I/O paradigms, allowing non-blocking operations that can improve the throughput of networked applications.
  • Ease of Use
    The library offers a clean and straightforward API with examples and documentation, which lowers the barrier to entry for developers who are new to network programming in Python.
  • Python Integration
    Being a Python library, socketify.py integrates well with existing Python applications and can be included as part of larger, multi-component systems.

Possible disadvantages of socketify.py

  • Limited Adoption
    As a relatively new or niche library, socketify.py might have a smaller user base and community compared to more established frameworks like Flask or Django, which could result in fewer community resources and third-party integrations.
  • Learning Curve
    For developers who are accustomed to synchronous programming paradigms, adapting to the asynchronous programming model of socketify.py may require an initial learning investment.
  • Documentation Depth
    While there is documentation, it might not be as extensive or comprehensive as those of more mature libraries, potentially requiring more experimentation or source code reading to fully grasp advanced features.
  • Potential Stability Issues
    Being less established, there might be undiscovered bugs or stability issues in production environments compared to long-standing Python networking libraries.
  • Ecosystem Limitations
    The library might lack some of the extensive third-party plugins or tools available in more popular frameworks, which could limit its extensibility.

DataPortia features and specs

  • OPC UA protocol
    Efficient data acquisition from automation systems via OPC UA protocol
  • Dashboard
    Real-time dashboard with gauges, charts, bar charts, and tables
  • Trends
    Interactive trend views with ECharts visualization and color customization
  • Reports
    Comprehensive reporting with CSV and PDF export
  • Automated reports
    Automated report scheduling (daily, weekly, monthly, custom)
  • AI analysis
    AI-powered data analysis with local Ollama LLM (anomalies, forecasts, reports)
  • Alarms analysis
    OPC UA Alarms & Conditions management with analytics and export
  • Web interface
    Web interface for all devices (Finnish/English/Swedish/German)
  • Multiplatform
    Supports linux and windows platforms
  • API Access
    API Interface for third-party systems

Analysis of socketify.py

Overall verdict

  • Socketify.py is a solid choice for developers seeking a high-performance web framework in Python, particularly for I/O-bound applications requiring speed comparable to frameworks in compiled languages, thanks to its use of uWebSockets under the hood.

Why this product is good

  • Built on uWebSockets, providing significant performance improvements over traditional Python web frameworks
  • Supports WebSockets natively, making it suitable for real-time applications
  • Lightweight and minimalistic design reduces overhead
  • Compatible with ASGI, allowing integration with existing Python async ecosystem
  • Active development and growing community support on GitHub
  • Good for building high-throughput APIs and services

Recommended for

  • Developers building real-time applications like chat apps or live notifications
  • Projects requiring high concurrency and low latency in Python
  • Teams looking to replace slower WSGI-based frameworks with something faster
  • Applications needing WebSocket support without heavy framework overhead
  • Microservices architectures where performance is critical
  • Python developers wanting an alternative to Node.js for performance-sensitive tasks

Analysis of DataPortia

Overall verdict

  • I don't have verified, up-to-date information about DataPortia at atorcom.fi, so I can't confirm its quality, reliability, or legitimacy. Before using or purchasing, it's recommended to research independently through reviews, company registration details, and user feedback.

Why this product is good

  • No verified public information or reviews were found for this specific product/service
  • Unable to confirm company legitimacy, security practices, or customer support quality
  • Cannot verify pricing, feature claims, or performance benchmarks without direct access to current data

Recommended for

  • Users should conduct independent due diligence, including checking domain registration history, business registration, and third-party reviews (e.g., Trustpilot, G2)
  • Consider reaching out to the company directly for references, case studies, or a trial before committing
  • Best suited for cautious buyers who verify data privacy policies and terms of service before use

Category Popularity

0-100% (relative to socketify.py and DataPortia)
Python
100 100%
0% 0
Reporting & Dashboard
0 0%
100% 100
Web Development
100 100%
0% 0
Automation
0 0%
100% 100

Questions & Answers

As answered by people managing socketify.py and DataPortia.

Who are some of the biggest customers of your product?

DataPortia's answer:

  • PCS-Engineering Oy (Finnish automation integrator and reseller partner)

DataPortia is an early-stage product currently used by industrial automation companies in Finland. Our reseller partner PCS-Engineering Oy deploys DataPortia for their industrial clients. We are actively expanding to energy plants, district heating networks, and manufacturing facilities across the Nordics and DACH regions.

What makes your product unique?

DataPortia's answer:

DataPortia is the only industrial data acquisition software that combines on-premises AI analytics with OPC UA connectivity โ€” all without any cloud dependency. What makes it unique:

  • Local AI analysis powered by Ollama LLM โ€” your process data never leaves your network. Supports anomaly detection, forecasting, cost optimization, and natural language queries directly on your production data.

  • Extreme throughput: handles 2,000+ measurement points per second across 10+ simultaneous OPC UA connections, storing up to 172 million rows per day in TimescaleDB.

  • True on-premises architecture โ€” no subscriptions to cloud services, no data leaving the plant. Critical for industries with strict cybersecurity and data sovereignty requirements.

  • 4-language UI (Finnish, English, Swedish, German) built in โ€” not bolted on. Every screen, tooltip, help page, and AI prompt works natively in all four languages.

  • Runs on commodity hardware โ€” PostgreSQL + TimescaleDB instead of expensive proprietary historian databases. Compresses 126 billion rows into ~1.2 TB.

Why should a person choose your product over its competitors?

DataPortia's answer:

Compared to alternatives like Ignition, WinCC, Wonderware, or AVEVA:

  • No cloud lock-in: Unlike cloud-based IoT platforms, DataPortia runs entirely on-premises. Your data stays in your network โ€” no recurring cloud fees, no vendor dependency.

  • Built-in AI analytics: Competitors require separate, expensive AI add-ons or cloud services. DataPortia includes local AI analysis (anomaly detection, forecasting, cost optimization) out of the box via Ollama.

  • Lower total cost: Uses open-source PostgreSQL/TimescaleDB instead of proprietary historian databases. No per-tag licensing โ€” connect unlimited measurement points.

  • OPC UA native: Connects to any OPC UA-compatible system (Siemens, ABB, Valmet, Beckhoff, Schneider, Honeywell, Rockwell) with built-in redundancy/failover.

  • Modern web interface: Responsive dashboards, interactive trends with drag-to-zoom, automated PDF/CSV reports โ€” accessible from any device without installing client software.

  • Free 30-day trial with full functionality, including AI features.

How would you describe the primary audience of your product?

DataPortia's answer:

DataPortia serves industrial professionals who need reliable, real-time process data โ€” without cloud complexity:

  • Automation engineers managing OPC UA-connected control systems (PLC, SCADA, DCS)

  • Plant managers at energy plants, district heating networks, and manufacturing facilities who need dashboards and automated reports

  • Process engineers in power generation, water treatment, waste incineration, and process industry who analyze trends and optimize operations

  • IT/OT professionals responsible for on-premises data infrastructure and cybersecurity compliance

  • System integrators deploying monitoring solutions for industrial clients (Siemens PCS7, ABB, Valmet, Beckhoff environments)

The common thread: organizations that handle sensitive industrial data and need powerful analytics without sending data to the cloud.

What's the story behind your product?

DataPortia's answer:

DataPortia was born from a real gap in the industrial automation market. Traditional SCADA historians and reporting tools are either prohibitively expensive, locked into proprietary ecosystems, or require cloud connectivity that many industrial facilities cannot accept for security reasons.

Built by Atorcom in Karstula, Finland, DataPortia was designed from the ground up to solve this: give industrial operators a modern, affordable, and secure way to collect, visualize, and analyze their automation data โ€” entirely on-premises.

The product evolved through direct experience with Finnish energy plants and process facilities, where the need for local AI analytics became clear. In 2025, DataPortia integrated Ollama-based local LLM analysis, making it one of the first industrial data tools to offer AI-powered anomaly detection, forecasting, and cost optimization without any cloud dependency.

Today, DataPortia connects to any OPC UA automation system and processes thousands of measurement points per second โ€” all running on standard PostgreSQL/TimescaleDB, proving that industrial-grade performance doesn't require enterprise-grade pricing.

Which are the primary technologies used for building your product?

DataPortia's answer:

  • ASP.NET Core 9.0 (.NET 9) โ€” Backend framework, self-hosted Kestrel server

  • PostgreSQL 18 + TimescaleDB โ€” Time-series database with hypertables, compression, and continuous aggregates

  • OPC UA (OPCFoundation.NetStandard) โ€” Industrial automation connectivity protocol

  • Ollama โ€” Local large language model runtime for on-premises AI analysis

  • Entity Framework Core 9.0 + Dapper โ€” ORM and raw SQL queries

  • ECharts 5.6 โ€” Interactive chart visualization (dashboards, trends, analysis)

  • Microsoft.Identity.Web โ€” Optional Azure AD authentication

User comments

Share your experience with using socketify.py and DataPortia. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, socketify.py seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

socketify.py mentions (2)

  • Show HN: Python framework is faster than Golang Fiber
    These "benchmarks" are useless, they're not testing anything real world except the performance of uWebsockets. There are copy errors all over the place. And then an advertisement: https://github.com/cirospaciari/socketify.py#briefcase-comme... Is this a professional framework that produces proper, real-world benchmarks and... - Source: Hacker News / over 3 years ago
  • This is how I started the development of the fastest ASGI and WSGI Server in TechEmPower Benchmarks
    After starting the project called socketify.py at https://github.com/cirospaciari/socketify.py, I got pretty good results and reviews, but many people asked if socketify.py could be used to create a WSGI and ASGI server. WSGI and ASGI have a lot of overhead, that's is why I choose not to use them in the first place, but adding an ASGI and WSGI server allows a lot of code already written to run faster! Source: over 3 years ago

DataPortia mentions (0)

We have not tracked any mentions of DataPortia yet. Tracking of DataPortia recommendations started around Mar 2026.

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