Compare Firebolt and Teradata to determine the best cloud data warehouse for your business. Explore pricing, performance, features, and use cases.

See why top data engineers and developers are switching to Firebolt for faster analytics, lower costs, and a better development experience. Try Firebolt for free.

‍

Quick Comparison Table

‍

Firebolt vs Teradata: Performance at Scale

Firebolt’s architecture is built for speed. Its decoupled storage and compute architecture enables sub-second query latencies even on terabytes of data and high-concurrency environments. Engines can be scaled horizontally to meet demand, and each query benefits from vectorized execution and adaptive indexing. Firebolt has demonstrated over 4,200 queries per second with sub-second latency in internal benchmarks.

Teradata, while known for handling massive workloads, is optimized for throughput, not latency. Traditional Teradata systems require significant tuning and provisioning to handle spiky or interactive workloads. Even in its newer VantageCloud Lake, performance tuning still requires careful configuration.

Built for Developers: APIs, SQL, and Flexibility

Firebolt was built with developers in mind. With a Postgres-compatible SQL dialect, REST APIs, a Python SDK, native dbt support, and GitOps-friendly workflows, engineers can fully automate and CI/CD their data infrastructure. Firebolt also supports workload isolation and provisioning via scripts.

Teradata, historically an enterprise system, has only recently integrated with dbt Cloud and begun offering REST APIs. While powerful, its development workflows are less friendly to modern DevOps practices and require specialized skills to optimize.

Firebolt supports Git-native workflows and Terraform-style provisioning, enabling developers to move fast without manual operations.

Scaling Without the Complexity

Firebolt allows instant vertical and horizontal scaling. Engines for separate workloads (e.g., ELT, ad hoc, production) can be spun up and scaled independently, all while accessing shared object storage. Customers have scaled from one month to 12 months of data without degrading performance.

Teradata scaling has traditionally meant adding more fixed infrastructure. VantageCloud Lake introduces some elasticity, but multi-cluster scale-out and workload isolation are more recent capabilities. Firebolt's architecture provides granular cost controls that support bursty or unpredictable workloads efficiently.

Pay for Performance, Not Overhead

With Firebolt, users pay only for what they use. Storage sits in low-cost object storage, and compute is billed per second based on engine size. Firebolt's indexing and compression can reduce storage requirements significantly. Customers have reported up to 77% lower storage costs and over 40% overall savings compared to previous solutions.

Teradata's cost structure includes software licensing, compute infrastructure, and enterprise-grade features—often with contractual commitments. For many interactive and variable workloads, Firebolt provides a more transparent and cost-efficient model.

Firebolt is Ideal For...

• Real-time analytics (low-latency dashboards)
  
  
• Embedded analytics (SaaS user-facing apps)
  
  
• High-concurrency applications
  
  
• ELT & dbt-based data pipelines
  
  
• DevOps & GitOps-integrated teams
  
  
• AI workloads such as LLM context retrieval
  
  

Firebolt is used across industries including retail, gaming, SaaS, and financial services, where low-latency and high-concurrency analytics are essential.

Migrate From Teradata to Firebolt with Confidence

Firebolt supports ANSI SQL with PostgreSQL-style syntax, making migration straightforward for most Teradata workloads. While Teradata-specific constructs like stored procedures or secondary indexes may require rework, core SQL translates easily. Firebolt integrates with dbt, Airflow, and Python SDKs for modern ELT and orchestration.

Typical migrations follow this path:

1. Export data from Teradata to object storage
   
   
2. Ingest into Firebolt using loaders or ELT tools
   
   
3. Rewrite queries using Postgres-compatible SQL
   
   
4. Rebuild transforms using dbt or orchestration tools
   
   

While Firebolt does not yet offer a public migration kit for Teradata, its support team and partners can assist throughout the process.

Firebolt vs Teradata: The Choice for the Modern Stack

Firebolt offers faster query performance, more flexible pricing, and a developer-centric experience. Teradata remains strong in high-throughput batch workloads but lacks the low-latency, high-concurrency performance required by modern, real-time applications.

Want to compare cost-performance against teradata?
Book a Firebolt demo to see what’s possible.

FAQ

Is Firebolt faster than Teradata?
Yes. Firebolt is optimized for low-latency, high-concurrency workloads, while Teradata is tuned for batch and throughput.

How does Firebolt pricing compare to Teradata?
Firebolt uses a usage-based, per-second billing model. Teradata has higher base costs, often tied to licensing and fixed infrastructure.

Does Firebolt support traditional SQL?
Yes. Firebolt supports ANSI SQL with PostgreSQL compatibility.

Can I migrate from Teradata to Firebolt easily?
Yes. Most SQL logic translates easily. Stored procedures and some proprietary features may require manual migration.

Which is better for developers: Firebolt or Teradata?
Firebolt. It offers a dev-first experience with modern APIs, SDKs, dbt integration, and CI/CD workflows.