OData vs GraphQL API: Key Differences for Enterprise Data Workflows

Why OData vs GraphQL Matters for Modern Enterprise Data Workflows? 

Choosing between OData and GraphQL has become a key decision for teams to build enterprise data workflows. Many organizations deal with scattered data, slow integrations, and inconsistent APIs. This challenge keeps growing as the average company now relies on more than 130 SaaS apps, a number that has doubled in the last five years, according to BetterCloud’s State of SaaS Report. 

At the same time, API expectations are rising fast. GraphQL adoption has picked up pace, with Apollo reporting that more than 60 percent of enterprises will run GraphQL in production by 2027:
  

With increasing data complexity and pressure to automate workflows, OData vs GraphQL has become an essential comparison for architects, developers, and integration teams. 

 

TL;DR – Key Takeaways 

• OData provides stable REST-style APIs well-suited for structured, predictable enterprise data. 

• GraphQL gives clients the flexibility to fetch exactly what they need, improving performance and reducing over-fetching. 

• By 2027, more than 60 percent of enterprises will run GraphQL in production. 

• Many teams succeed with a hybrid approach, using OData for legacy and structured systems and GraphQL for modern, dynamic workloads. 

• eZintegrations™ helps unify both protocols, enabling easy orchestration and streamlined data workflows. 

 

What is OData? 

OData (Open Data Protocol) is a standard for building RESTful APIs. It uses familiar HTTP methods and offers rich querying features like filtering, pagination, sorting, and expansion operations. Its structure fits naturally with relational databases and table-based systems. 

Why has OData been popular in enterprises? 

OData is stable, predictable, and aligns closely with enterprise systems built on SQL-like architectures. Organizations using Microsoft or SAP often rely on OData because it maps cleanly to existing schemas and works well for CRUD operations. 

For tasks like retrieving customer lists, inventory records, or order data, OData offers clear endpoints and a consistent pattern.
Its limitations appear when clients need nested or cross-entity data, or when the data needs to grow more dynamic. This is where GraphQL becomes compelling. 

 

What is GraphQL? 

GraphQL is a query language and runtime that lets clients define exactly what data they need. Instead of multiple endpoints, it exposes a single schema. Clients send one query and receive the precise structure they asked for. 

Why are many enterprises adopting GraphQL now? 

GraphQL adoption is rising quickly. Industry surveys show nearly 70 percent of organizations use GraphQL in some part of their stack, and the majority say it exceeded performance and development expectations. 

GraphQL fits well with modern application needs, especially when data is deeply nested, dynamic, or consumed by multiple front ends. It avoids over-fetching and boosts efficiency across teams building front-end apps, mobile apps, and AI-driven experiences. 

GraphQL isn’t simple. It requires careful schema design, strict versioning control, and strong security. But in return, teams get a flexible and modern API foundation. 

 

Why compare OData vs GraphQL for enterprise data workflows? 

When teams design integrations or workflows across systems, they often ask: Should we stay with OData or introduce GraphQL? 

Here’s how both compare across the most important areas. 

 

Data Modeling and Complexity 

OData fits structured, table-based models with predictable schemas.
GraphQL fits complex, interconnected data structures with nested relationships. 

If your data is flat and stable, OData works well. If your data is dynamic or needs to be presented differently to multiple clients, GraphQL is the better choice. 

 

Query Flexibility and Performance 

GraphQL lets clients fetch only what they need, which improves performance and reduces unnecessary payloads. 

OData may require multiple endpoints or can lead to over-fetching when consumers want varied data views. 

Many enterprises adopting GraphQL report faster release cycles and smoother development workflows. 

 

Ecosystem and Tooling 

OData works well inside Microsoft, SAP, and other legacy ecosystems.
GraphQL thrives in modern architectures with microservices, API federation, and cloud-native tooling. 

 

Security, Governance, and Compliance 

OData aligns with traditional governance models based on endpoint-level controls.
GraphQL requires additional safeguards like query depth limits and schema-level access checks. 

Both can be secured well with proper design, but GraphQL needs more discipline at the start. 

 

How to decide between OData and GraphQL? 

Most enterprises benefit from using both, depending on context. 

Use OData when: 

• You rely on structured and relational datasets 

• Your systems run on Microsoft or SAP 

• You prioritize stable REST endpoints 

• Auditability and predictable schemas matter 

Use GraphQL when: 

• You need flexible, customized data endpoints 

• You deal with nested or dynamic data 

• You want to unify multiple backend systems 

• You want to cut down on bandwidth usage 

Consider a hybrid strategy when: 

• You’re modernizing legacy systems 

• You want flexibility without losing reliability 

• You want to migrate gradually to modern APIs 

This is where eZintegrations™ plays a powerful role. 

 

OData vs GraphQL API: Key Differences 

How eZintegrations™ Simplifies Data Workflows with OData and GraphQL? 

Enterprise systems rarely follow one protocol. Most teams use a blend of legacy systems, modern SaaS platforms, and data services. 

eZintegrations™ helps by: 

• Connecting to OData, GraphQL, REST, and other APIs 

• Orchestrating end-to-end data workflows across systems 

• Normalizing and transforming APIs into unified schemas 

• Supporting governance, versioning, and auditing 

• Enabling a gradual transition from legacy OData systems to GraphQL-powered experiences 

Teams can expose GraphQL on top of older systems, maintain OData endpoints, or unify everything through one platform. 

 

What’s the Best Way Forward with OData vs GraphQL? 

There’s no one-size-fits-all answer. OData fits structured data and legacy systems.  GraphQL fits flexible, high-speed, modern experiences. 

Most enterprises see the best results with a hybrid approach. Platforms like eZintegrations™ help teams modernize workflows, unify APIs, and automate data movement without disruption. 

If you’re looking to simplify integrations or modernize API workflows, consider trying eZintegrations™. Ready to simplify your data workflows?

Book a quick demo of eZintegrations™ today and see how easily you can connect systems, automate data movement, and modernize your API stack without heavy engineering work. 

 

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• OData Api vs REST Api : Key Differences for Enterprise Integrations 

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• Why do U.S. Teams Still Struggle with Data Readiness for AI in 2025? 

• Traditional Data Integrations vs Automated AI Pipelines: Which one is better in 2026? 

• ETL vs ELT Difference: Which Approach Fits into Modern AI Workflows 

 

 

Frequently Asked Questions (FAQ) 

Q: What is the main difference between OData and GraphQL?
OData uses RESTful endpoints for structured data. GraphQL lets clients shape the response based on their exact needs. 

Q: Can OData and GraphQL coexist?
Yes. Many enterprises combine both using OData for legacy data and GraphQL for modern apps. 

Q: Does GraphQL offer better performance?
Often, yes, because it avoids over-fetching and tailors responses precisely. 

Q: Are there security concerns with GraphQL?
GraphQL needs strong schema governance, access control, and query limits. 

Q: How does eZintegrations™ help in the transition?
It connects to both OData and GraphQL, orchestrates workflows, and helps teams modernize without rewriting systems.