The legal industry is undergoing a data revolution. From AI to financial forecasting, law firms must harness the power of data to remain competitive. But as firms consider modernizing their data strategy, a pivotal question emerges: should they invest in a turnkey data lakehouse solution or develop their own in-house system?
This is not a simple cost comparison—it’s a strategic decision with long-term implications. Below, we break down the key factors law firms should consider when weighing the buy vs. build question.
1. Sustainability
Buying a Data Lakehouse Product: A vendor-managed solution ensures seamless updates, compliance, and optimizations, reducing the strain on internal teams. Law firms can maintain their focus on client service rather than IT infrastructure. Vendors also ensure that the technology remains up-to-date with industry standards and regulations, eliminating the burden of constant monitoring and adaptation.
Moreover, vendor solutions benefit from economies of scale—leveraging best practices and collective improvements from a broader customer base of peer firms. This means firms not only get cutting-edge updates but also enhancements that stem from industry-wide use cases and research.
Building Your Own Data Lakehouse: Maintaining an in-house system requires a highly specialized and dedicated Lakehouse team to manage updates, security, and compliance—tasks that can become increasingly complex over time. Firms must invest in hiring skilled professionals and developing best practices for continuous improvement, which can divert resources from core legal functions.
Additionally, homegrown solutions often suffer from knowledge silos. When key developers leave, firms risk losing institutional knowledge critical for ongoing system maintenance and improvements. Without a structured approach to documentation and continuity planning, long-term sustainability becomes a challenge.
2. Scalability
Buying: Pre-built solutions are designed for enterprise-scale growth, providing flexibility without significant additional investment in infrastructure. Vendors optimize their products for scalability, meaning that firms can easily adjust capacity based on demand without incurring high costs or technical overhead.
Building: While a custom-built solution allows for tailored expansion, scaling effectively requires careful long-term planning and significant resources. Custom solutions often need constant reengineering to accommodate increased data volume and new technological advancements, adding complexity and cost.
3. Security
Buying: Vendor solutions incorporate enterprise-grade security and compliance measures, benefiting from continuous improvements and external audits. These solutions typically adhere to strict legal and data privacy standards, helping law firms maintain regulatory compliance effortlessly.
Many vendors are certified in major regulatory frameworks such as SOC 2, ensuring that firms meet compliance obligations without dedicating internal resources to security audits and penetration testing.
Building: Ensuring top-tier security in a custom-built cloud lakehouse system is a full-time job—one that requires specialized expertise and constant vigilance. For most law firms, managing this in-house is a significant operational burden.
4. Cost Considerations: Staffing vs. Licensing
Every law firm, no matter how large, has limits on hiring. Firms must be strategic about where they allocate their full-time employees (FTEs). The critical question is: Do you want to spend valuable FTEs on building and maintaining the data infrastructure—the plumbing—or would you rather allocate them to higher-value tasks such as analytics, AI, and other initiatives that directly leverage the data to drive business impact?
As you consider the buy vs. build decision and overall cost, it extends beyond just the initial investment. When building in-house, firms must not only consider infrastructure but also the significant staffing requirements. Hiring the right talent is crucial, and law firms will need to recruit and retain a team with specialized expertise in data engineering, cloud architecture, and security. Here are typical roles and their estimated salaries:
Role | Estimated Salary |
Azure Cloud Architect | $192,000 |
Azure Senior Data Engineer | $175,200 |
Azure Data Engineer | $144,000 |
Azure DBA | $120,000 |
Azure Data Analyst | $98,400 |
Azure Security Specialist | $150,000 |
Total Estimated Salary Cost: $879,600
Beyond base salaries, additional costs such as benefits, ongoing training, turnover, and recruitment fees must be factored in, making staffing a significant and ongoing expense.
Buying: A vendor-provided solution, by contrast, offers a predictable pricing model. Some solutions operate on a subscription basis, bundling security, support, and continuous updates into the cost. Firms buying a lakehouse solution might expect to pay 1/3 to 1/2 the cost of internally staffing & building their own.
When comparing staffing costs against licensing a pre-built lakehouse solution, firms should consider the ongoing commitment required to sustain an internal team versus the convenience of outsourcing development and maintenance to an established vendor. With a vendor solution, firms can focus on leveraging the data, instead of managing IT infrastructure. Additionally, vendor pricing models offer predictable cost structures, reducing financial uncertainty.
5. Time to Deployment
Buying: Pre-built solutions can be deployed quickly, allowing firms to start leveraging data capabilities sooner. Some vendors offer rapid deployment frameworks that enable organizations to integrate data and begin using analytics within weeks or months.
Building: Developing a system from scratch requires time for design, development, and testing, delaying potential benefits. According to industry experts, building a fully functional data lakehouse can take well over 12 months, depending on the complexity of the requirements and available resources. Additionally, unexpected delays can arise due to hiring challenges, integration issues, and evolving regulatory requirements, all of which prolong the deployment timeline.
6. Customization
One of the most appealing aspects of building a lakehouse in-house is the ability to create a solution that is tailor-made for the firm’s exact specifications. With full control over data architecture, governance models, and security protocols, firms can ensure that their data infrastructure aligns perfectly with their specific business needs. This level of customization can be highly advantageous for firms with unique workflows or stringent compliance requirements.
However, this flexibility comes at a cost. Developing a fully customized system requires a significant investment in both time and resources. It often necessitates hiring a larger in-house team or engaging expensive external consultants to design, implement, and maintain the system. Customization efforts can also introduce long-term technical debt, as evolving business needs may require continual modifications and enhancements that demand further development efforts.
Buying: Many modern lakehouse solutions offer robust configuration options, enabling firms to tailor key aspects of the platform to their needs while still benefiting from vendor-driven innovation, security, and scalability.
Building: While a custom-built system allows for complete control, law firms should carefully assess whether the benefits of full customization outweigh the financial and operational burdens that come with maintaining an entirely bespoke data infrastructure.
7. Vendor Support
Buying: Vendors provide dedicated support teams, training, and regular updates, ensuring law firms stay ahead of potential issues. Many vendors offer round-the-clock technical support, software patches, and compliance updates, reducing the burden on internal IT teams.
Building: Internal IT teams bear full responsibility for support and troubleshooting, which can divert focus from other priorities. Law firms that choose to build must be prepared to establish their own support frameworks and develop internal expertise to resolve technical challenges.
8. Integration
Buying: Vendor solutions typically include pre-built integrations with many legal-specific systems, ensuring seamless connectivity with case management, document automation, e-discovery, and compliance platforms. Moreover, vendors continually expand their integration libraries based on customer needs, meaning law firms benefit from a faster-growing ecosystem of compatible tools.
Building: In-house teams must manually build and maintain integrations with other systems, a task that is both time-intensive and technically complex. While firms can prioritize the integrations they deem most critical, their pace of development will almost always lag behind that of a vendor with a dedicated team focused solely on expanding data connectivity.
9. Innovation
Buying: Vendors invest in research and development, ensuring their solutions remain current with technological advancements. Additionally, firms that buy a vendor solution benefit from the collective intelligence and innovation that comes from the vendor’s entire customer base. Features and improvements are driven by real-world use cases across multiple industries, allowing law firms to leverage best practices and advancements that they may not have considered on their own.
Building: Keeping an in-house system innovative requires dedicated resources and a continuous commitment to evolving technology. Since internal teams are solely responsible for idea generation, law firms may face limitations in anticipating future needs or uncovering emerging trends. Without external influence, in-house solutions run the risk of stagnation, missing out on innovative enhancements that a broader user base naturally helps drive.
10. The SQL Fallacy
Most every law firm has their version of a SQL MDP, Master Data Platform. Firms assume that their experience managing SQL-based data warehouses equips them to build a data lakehouse. However, these are fundamentally different technologies.
SQL knowledge does not directly translate to building a modern lakehouse, which requires expertise in distributed computing, storage management, and AI-driven analytics.
Workload Realities: Existing IT staff are already working full-time on their current responsibilities. Expecting them to upskill from SQL to an Azure Lakehouse while continuing to fulfill their existing duties and simultaneously architecting and implementing a new data infrastructure is an unrealistic expectation that can lead to burnout, inefficiencies, and project failure.
Firms considering a custom-built solution should carefully assess whether they have the necessary in-house capabilities or if their resources would be better allocated elsewhere.
Conclusion
Choosing between buying and building a data lakehouse is a strategic decision that depends on a firm’s long-term vision, resources, and priorities. While building offers control and customization, it requires significant investment in expertise, infrastructure, and ongoing maintenance. On the other hand, vendor-backed solutions provide a faster, more secure, and scalable path to leveraging data effectively.
Law firms should weigh the trade-offs carefully, ensuring that their decision aligns with their broader business goals. By considering factors such as sustainability, cost, security, and innovation, firms can position themselves to maximize the value of their data infrastructure without unnecessary complexity.