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Why do you need to pay more just to access your own marketing data?
For many analysts and marketing teams, traditional SaaS connectors often come with frustrating limitations, high costs, rigid pricing models, and limited control over what’s happening behind the scenes. If you’ve ever hit a field cap or waited weeks for a support ticket, you’re not alone.
We built a free, open-source connectors library to fix that. It’s for analysts who want transparency, for marketers who need flexibility, and for teams that value control over their data pipelines. No black boxes. No surprise fees. Just clean, customizable, and scalable integration, on your terms.
SaaS data connectors promise convenience, but come with hidden trade-offs. From rising costs to limited flexibility, they often create more problems than they solve. Let’s break down the key issues analysts and marketing teams face when relying on these tools.
Traditional connectors often come with usage-based pricing and hidden fees. Costs rise quickly as you add data sources or increase volume. Even small changes can trigger higher bills. For growing teams, this makes scaling unpredictable and forces tough trade-offs between full reporting and staying within budget.
Most SaaS connectors do not clearly show how your data is processed. You can’t verify the logic, resolve issues, or tailor it to your needs. You're tied to their system, pricing, and update rules, making it hard to scale or stay flexible as your reporting needs evolve.
Traditional SaaS connectors are rigid; they rarely let you tailor how data is mapped, transformed, or filtered. As marketing strategies change, you're stuck waiting for vendors or paying extra for new features. Custom requirements become bottlenecks, not opportunities, forcing analysts to work around limitations instead of having tools adapt to them.
Many SaaS tools fail to keep systems truly connected. Integration gaps result in delayed updates, missing fields, and inconsistent data across platforms. Over time, this slows down reporting, increases manual work, and makes it harder for teams to trust the numbers they rely on every day.
As your data and integrations grow, traditional SaaS connectors often struggle to keep up. They struggle to handle increased volume, leading to slow syncs or failed jobs. You hit performance ceilings and must pay more for higher tiers, yet still face the same limitations. It’s a costly bottleneck that stalls your team’s growth plans.
Many SaaS connector tools appear affordable at first, but the real cost often becomes apparent later. Let’s examine a few popular tools and identify where they fall short.
Funnel.io’s FlexPoints system charges based on the number of connectors, fields, and destinations. What starts as flexible quickly turns into a budgeting headache. As you add sources or dimensions, points vanish fast, often requiring upgrades or manual monitoring to avoid overages. Costs can spike unexpectedly as reporting needs grow.
Supermetrics uses a tiered pricing model where you pay for each connector, destination, and refresh option. Lower plans limit the number of fields and metrics you can access. As your needs grow, you’ll need to upgrade just to unlock standard features. This makes scaling expensive and harder to manage.
Coupler.io offers easy, no-code integrations, but lacks in-depth customization options. Advanced transformations require consulting services or manual workarounds. As reporting needs grow, such as the need for custom workflows or automation, the tool’s limitations become apparent, leading to increased costs and operational friction. For complex use cases, this creates growing risk and inefficiency.
Not all data connectors are built for control or growth. Unlike SaaS tools, open-source options offer full visibility, flexibility, and ownership. Here’s how they solve the problems listed above.
With open source, you're in full control. You can view, edit, and version every part of the connector. When APIs change or new fields are introduced, you can update the code instantly, eliminating vendor delays and guesswork. Everything is transparent, adaptable, and built to match your data needs.
Open-source connectors enable you to adapt instantly when APIs change or new data is required. Instead of waiting for vendor updates, you can customize mappings, add custom fields, or connect unique systems yourself. This flexibility means your integrations evolve with your workflows, without delays or additional costs.
Open-source connectors improve through community collaboration. Developers and analysts contribute by adding new sources, fixing bugs, and enhancing features. This shared effort creates a fast-evolving ecosystem that meets real-world needs, often more reliably and quickly than closed vendor systems.
Open-source connectors eliminate licensing fees, allowing teams to scale integrations without unexpected costs. You’re free to add data sources or ramp up syncs without worrying about usage tiers. This DIY model delivers significant long-term savings, especially for startups and SMEs with tight budgets.
Open-source connectors offer full visibility into how data is handled, allowing teams to audit transformations, control access, and apply their own security standards. This transparency supports compliance needs, making it easier to meet internal policies and external regulations without relying on third-party black boxes.
Not every team has the budget for premium tools or the time to work around their limits. Open-source connectors offer flexibility, control, and cost savings across roles. Here’s how different teams benefit.
Open-source connectors provide analysts with complete visibility and control over their ETL pipelines, enabling them to debug, refine, and enhance data flows to create richer and more accurate insights. This independence accelerates analysis and ensures that reports align with real-world needs, helping marketing teams deliver precision-driven insights on time.
Open-source connectors enable Marketing and RevOps teams to bring data from ad platforms, CRMs, and analytics into unified dashboards, without requiring coding or expensive tools. They get real-time campaign metrics, simplify tracking, and reduce reliance on IT. This enables faster insights and better decision-making.
Small businesses and startups often face tight budgets and can’t afford costly SaaS tools. Open-source connectors offer a free way to integrate ad platforms, CRMs, and data warehouses. They allow these teams to scale operations, automate reporting, and access quality data, without increasing costs or relying on paid platforms.
OWOX connectors are more than just open-source; they’re designed with real marketing and analytics workflows in mind. Here’s what makes this library stand out.
OWOX connectors run on open-source Apps Script and JavaScript, allowing you to read, modify, and extend the code as needed. You're not tied to fixed setups; you can adjust connectors to match your tools, data structure, and reporting needs without relying on vendor updates or limitations.
The library includes working connectors for X (Twitter), LinkedIn, Facebook Ads, and Open Exchange Rates. You can bring in campaign performance and currency data directly, without requiring any extra tools or coding. It’s built to help analysts quickly and reliably access the key numbers they need.
OWOX is expanding its connector library to cover CRM and accounting platforms. That means teams will soon be able to sync sales, finance, and marketing data in one place, enabling them to build comprehensive, connected reports without switching between tools or incurring multiple system costs.
Everything is open on GitHub, including current features, upcoming updates, and ideas from the community. Anyone can raise issues, request features, or contribute code. This keeps the library evolving based on real user needs, not vendor priorities.
OWOX connectors send data directly to BigQuery and Looker Studio, eliminating the need for extra steps or software. You can build dashboards and run SQL reports on fresh data, without waiting for manual exports or third-party syncing tools. It’s smooth, direct, and reliable.
Modern analytics workflows demand tools that are adaptable, transparent, and easy to integrate. Open-source connectors meet these needs by fitting into every layer of the stack, without adding complexity or cost. Here's where they make the biggest impact.
Open-source connectors plug directly into modern data stacks, integrating with warehouses like BigQuery, transformation tools, and BI platforms. Built as independent, cloud-native modules, they offer flexibility to scale, replace, or extend components without vendor lock-in, supporting ever-evolving data ecosystems.
Open-source connectors make data pipelines clear and customizable, so teams don’t have to rely on engineers for every change. With accurate, real-time data flowing into familiar tools, non-technical users can explore insights, build reports, and make decisions faster without bottlenecks or long support queues.
These connectors work well with orchestration tools, enabling teams to automate data workflows, manage version control, and establish access rules. This setup supports compliance and governance while providing teams with full control, without being tied to any specific vendor or platform.
Open-source connectors integrate seamlessly with monitoring tools, providing teams with full visibility into every step of the data flow. You can identify failures, detect data issues early, and resolve problems quickly. This enhances reliability and ensures reports remain accurate, consistent, and trusted throughout the business.
The OWOX Data Marts (Community Edition) is designed for teams who want full control over their marketing data without relying on expensive tools or rigid platforms. It extends beyond the Apps Script version, offering support for cloud data warehouses such as Snowflake, Databricks, and Azure Synapse.
Analysts can manage data marts, define a semantic layer, and deliver insights directly into Sheets, Looker Studio, or Excel. With advanced scheduling and zero licensing fees, it’s a future-proof solution for data autonomy.Check out our GitHub repository to view available connectors, setup instructions, and contribution guidelines.
