A deep-dive into the top Terraform providers that let teams manage modern data infrastructure as code in 2025. Learn which option fits Snowflake, Databricks, BigQuery, MongoDB Atlas, Confluent, Redshift, ClickHouse, Yugabyte, Timescale, or PostgreSQL workloads and how to pick the right tool for cost, scale, and governance.
The best Terraform providers for data infrastructure in 2025 are the Snowflake Provider, the Databricks Provider, and the BigQuery Provider. The Snowflake Provider excels at fine-grained governance; the Databricks Provider offers unified compute and AI pipelines; the BigQuery Provider is ideal for serverless analytics at petabyte scale.
In 2025, cloud data stacks evolve weekly. Treating databases, warehouses, and streaming clusters as code lets teams version, review, and roll back changes just like application releases.
Terraform remains the de-facto standard because it supports dozens of data platforms, enforces policy as code, and integrates with CI pipelines.
Our research weighted seven factors equally: feature depth, ease of use, pricing clarity, performance, integration footprint, community momentum, and enterprise support. Products received additional credit for new 2025 capabilities such as object tagging APIs, zero-ETL pipelines, or native CI modules.
Snowflake Terraform Provider
Snowflake’s provider reached version 1.0 in early 2025 and now exposes every security, storage, and computational object. Engineers can codify storage integrations, row-level policies, and even dynamic data masking. Native modules speed up multi-account deployments and SSO rollouts.
Databricks refactored its provider to support Unity Catalog, Lakehouse Federation, and GenAI Model Serving in 2025.
Workspaces, job clusters, and MLflow models are first-class resources, allowing teams to spin up complete analytics stacks from a single plan.
Google’s provider now supports column-level encryption keys and Dataform repositories. Serverless architecture means zero cluster management while the provider ensures dataset IAM, scheduled queries, and cross-project sharing stay predictable across environments.
Atlas added serverless instances, multi-cloud clusters, and encrypted persistent snapshots in its 2025 provider update.
Teams manage network peering, private endpoints, and search indexes alongside databases for consistent security posture.
Streaming pipelines benefit from declarative Kafka topics, RBAC roles, and Schema Registry compatibility. The 2025 release added Stream Governance and Inline SQL Transforms, reducing day-two ops work.
While Redshift is managed via the broader AWS provider, 2025 modules abstract subnet groups, RA3 scaling, and zero-ETL integrations with Aurora.
Engineers can version workload management queues and pause-resume schedules to cut costs.
ClickHouse Cloud’s new provider codifies services, users, and tiered storage layering. Fast cluster spin-ups make it attractive for latency-sensitive analytics while object-level grants tighten governance.
Yugabyte’s distributed Postgres API offers geo-sharded databases through Terraform resources for universes, xCluster replication, and TLS rotation. Open source roots plus enterprise support make it popular for hybrid deployments.
TimescaleDB Terraform Provider
Timescale’s 2025 provider introduces autoscaled hypertable services and continuous aggregates. Teams capture detailed observability metrics via Terraform-managed Prometheus endpoints.
The community provider lets Ops teams declaratively manage roles, extensions, and databases for self-hosted Postgres. New 2025 features include logical replication slots and pgAudit configuration resources.
Start with your dominant workload. Warehouses favor Snowflake or BigQuery, while unified analytics pipelines gravitate to Databricks. Streaming-heavy stacks lean on Confluent.
Self-hosted environments may prefer PostgreSQL or Yugabyte for full control. Map governance requirements to provider maturity: if column masking and policy automation are critical, Snowflake wins.
Separate state files per environment, enable drift detection with continuous runs, and use tested community modules where possible. Enforce policy checks (OPA or Sentinel) so every merge protects PII.
Finally, integrate query tools like Galaxy to validate schema changes against real workloads before applying.
Galaxy sits at the query layer, not the infrastructure layer. Once your Terraform plan provisions Snowflake or Databricks, Galaxy’s developer-first SQL IDE lets engineers and analysts explore those environments safely. Versioned queries, AI-assisted refactors, and workspace sharing complement the infrastructure-as-code discipline, ensuring both the data stack and the SQL that powers it remain auditable.
.
Database as code means declaring every database object - from users to tables - in version controlled files. Terraform then provisions or updates those resources so infrastructure changes follow the same review and rollback process as application code.
The Google BigQuery provider is often the fastest to learn because BigQuery is serverless. Teams manage datasets and IAM without configuring clusters, which reduces the number of Terraform resources they must understand.
Terraform provisions the data platform while Galaxy governs the SQL layer. Once Snowflake or Databricks is spun up, Galaxy’s IDE lets engineers write, review, and version queries against that infrastructure, closing the loop between deployment and analytics.
Yes. Terraform supports multiple providers and workspaces, so you can orchestrate Snowflake, Confluent, and MongoDB Atlas from the same codebase while keeping state files isolated per environment.
.avif)
.avif){kind=logo}
