Data Warehouses

Databricks vs BigQuery

Compare Databricks and BigQuery side-by-side. See feature differences and pricing in the Data Warehouses category.

No reviews yet

Pricing: Pay as you go per DBU; rates vary by cloud, tier and region. SQL warehouses on AWS Premium: Classic $0.22, Pro $0.55, Serverless $0.70 per DBU. 14-day trial; commitments by quote.

Databricks is a data lakehouse platform for SQL warehousing, data engineering, machine learning and AI agents on open table formats, sold pay as you go.

17 /18 features Full profile

BigQuery

by Google

No reviews yet

Pricing: Free usage tier of 1 TiB of queries and 10 GiB of storage a month. On-demand queries $6.25 per TiB; editions from $0.04 per slot-hour pay as you go. Storage per GiB.

BigQuery is Google Cloud's serverless data warehouse for SQL analytics, machine learning and streaming data, billed by data scanned or by slot capacity.

18 /18 features Full profile

Feature Comparison

Data Warehouses features side-by-side

Feature	Databricks 17/18 features	BigQuery 18/18 features
Independent scaling of storage and compute Compute clusters resized or paused without moving data, and storage billed separately.	Yes	Yes
Serverless query execution Queries run on capacity the service allocates per query, with no cluster to provision.	Yes	Yes
Multi-cluster concurrency scaling Extra compute clusters spin up automatically when query queues form and spin down after.	Yes	Yes
Time travel to prior table states Query or restore a table as it was at any point within a retention window of days.	Yes	Yes
Zero-copy cloning of databases A full copy of a database or table created instantly by sharing the underlying storage.	Yes	Yes
Auto-refreshing materialized views Materialized views kept current by the service, incrementally where possible.	Yes	Yes
Native semi-structured columns JSON, Avro or Parquet loaded into a variant-style column and queried by path.	Yes	Yes
External tables on data lake files Files in object storage queried in place as tables in open formats.	Yes	Yes
Open table format interoperability Warehouse tables stored in an open format such as Iceberg that outside engines can read.	Yes	Yes
Streaming row ingestion into tables Rows inserted continuously from streams or landing files, without scheduled batch loads.	Yes	Yes
Live data sharing across accounts Tables shared with another account or organization as live reads, without copying data.	Yes	Yes
Column masking policies Sensitive columns masked dynamically per role at query time.	Yes	Yes
Row access policies Row-level filters applied per role or user by the warehouse itself.	Yes	Yes
Automatic query result reuse Repeated identical queries served from a result cache without recomputation.	Yes	Yes
Workload management queues Queries assigned to resource groups with priorities, memory limits and concurrency caps.	No	Yes
Compute spend limits and alerts Budgets or resource monitors that alert on, or suspend, compute past a spend threshold.	Yes	Yes
Cross-region warehouse replication Databases replicated to another region or cloud with failover for disaster recovery.	Yes	Yes
In-warehouse Python execution Python code runs inside the warehouse as functions or procedures next to the data.	Yes	Yes
Overall Rating	No reviews yet	No reviews yet

Databricks 17/18 features

Independent scaling of storage and compute: Yes
Serverless query execution: Yes
Multi-cluster concurrency scaling: Yes
Time travel to prior table states: Yes
Zero-copy cloning of databases: Yes
Auto-refreshing materialized views: Yes
Native semi-structured columns: Yes
External tables on data lake files: Yes
Open table format interoperability: Yes
Streaming row ingestion into tables: Yes
Live data sharing across accounts: Yes
Column masking policies: Yes
Row access policies: Yes
Automatic query result reuse: Yes
Workload management queues: No
Compute spend limits and alerts: Yes
Cross-region warehouse replication: Yes
In-warehouse Python execution: Yes

No reviews yet

BigQuery 18/18 features

Independent scaling of storage and compute: Yes
Serverless query execution: Yes
Multi-cluster concurrency scaling: Yes
Time travel to prior table states: Yes
Zero-copy cloning of databases: Yes
Auto-refreshing materialized views: Yes
Native semi-structured columns: Yes
External tables on data lake files: Yes
Open table format interoperability: Yes
Streaming row ingestion into tables: Yes
Live data sharing across accounts: Yes
Column masking policies: Yes
Row access policies: Yes
Automatic query result reuse: Yes
Workload management queues: Yes
Compute spend limits and alerts: Yes
Cross-region warehouse replication: Yes
In-warehouse Python execution: Yes

No reviews yet

Pricing

Databricks

Pay as you go per DBU; rates vary by cloud, tier and region. SQL warehouses on AWS Premium: Classic $0.22, Pro $0.55, Serverless $0.70 per DBU. 14-day trial; commitments by quote.

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BigQuery

Free usage tier of 1 TiB of queries and 10 GiB of storage a month. On-demand queries $6.25 per TiB; editions from $0.04 per slot-hour pay as you go. Storage per GiB.

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