Table of Contents

Findings from 100+ data professionals on when to build in-house versus buy vendor solutions

Introduction

Each month, we run a brief survey through our newsletter and social channels to capture what’s top of mind for today’s data teams. The goal is to share actionable benchmarks and peer-driven insights that can help you fine-tune your data stack. These reports aim to reflect the shifting priorities and real-world challenges faced by professionals in engineering, analytics, and operations.

This month, we explored the classic decision point of Build vs Buy in the data stack. Should teams invest in building custom solutions that maximize control and flexibility, or lean on vendor-managed platforms that promise speed and scalability? The answers reveal how teams weigh cost, ownership, and long-term tradeoffs.

To better understand how companies are making these decisions, we sent out a survey to our subscribers, with 102 data professionals submitting responses. Here’s what they shared.

Why This Survey Matters

The Build vs Buy debate has shaped the modern data stack since its inception. As tools proliferate, the question of whether to rely on vendors or build internally has become even more pressing. Vendor-managed solutions accelerate time-to-value but can introduce lock-in and unpredictable costs. Internal builds provide control and customization but require ongoing investment in maintenance and expertise.

Our findings show that most teams are opting for a hybrid strategy: buying vendor solutions for commoditized areas of the stack, while building selectively for functions requiring customization or compliance. This signifies a shift toward pragmatism, not ideology, in how data leaders approach tooling.

Methodology

This report is based on a survey distributed through our newsletter and partner channels, reaching professionals across data engineering, analytics, product, and operations roles.

  • Respondents: 102

  • Company sizes: Ranging from startups to global enterprises

  • Industries: SaaS, fintech, retail, healthcare, manufacturing, and media

Key Takeaways

  • 61% of teams take a buy-first, build-selectively approach

  • The top reasons to build are control/customization (64%) and compliance (42%)

  • The top reasons to buy are faster time-to-value (71%) and reduced maintenance burden (58%)

  • Teams are most likely to build in transformation/orchestration and buy storage and ingestion

  • 29% reported regretting a build decision, while 18% regretted a buy decision in the past year

  • The biggest challenge in decision-making is uncertainty about ROI (36%)

Results and Insights

Overall Approach: Build vs Buy

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Insight
The dominant pattern is “buy-first, build when necessary.” This suggests pragmatism: teams want speed and stability from vendors, but will build when gaps or compliance requirements arise.

Why Teams Build

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Insight
Building is driven by necessity more than savings. Teams build when vendor offerings fall short, especially in regulated industries.

Why Teams Buy

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Insight
Buying is about efficiency. Teams want to focus on insights, not infrastructure upkeep.

Where Teams Build vs Buy


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Insight
Transformation is most often built in-house, where company-specific logic matters. In contrast, commoditized layers like storage are dominated by vendors.

Regrets and Challenges

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Biggest challenges when deciding:

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Insight
Build regret is more common than build regret, often tied to underestimated maintenance costs. Vendor regret usually centers on pricing or lock-in.

Final Thoughts

The Build vs Buy debate is no longer about choosing one side; it’s about balance. Teams are increasingly blending vendor solutions with selective internal builds to get the best of both worlds.

The takeaway: vendor solutions dominate in areas where scale and reliability are critical, while internal builds thrive where customization or compliance are non-negotiable. The future of the data stack looks less like “build vs buy” and more like “build and buy, strategically.”

About Integrate.io

Integrate.io helps data teams simplify their build vs buy decisions by offering a flexible, low-code platform for data ingestion, transformation, and orchestration. Teams can consolidate multiple functions into one platform, reduce maintenance overhead, and gain faster time-to-value, without giving up control.

Ready to see how Integrate.io can fit into your stack? Request a demo