data
34 articles on data — what drives the cost, how it is priced, and where the savings actually are.
Data warehouse cost compared: Redshift vs BigQuery vs Synapse
Redshift, BigQuery, and Synapse price data warehousing on different axes, provisioned nodes or serverless, per-TB-scanned or per-slot, per-DWU. The cheapest depends on query pattern and volume, not the platform. This compares the models.
GCP BigQuery storage cost: active, long-term, and physical billing
BigQuery storage bills active data (recently modified) at about $0.02/GB-month and long-term data (untouched 90 days) at about half that, with an option to bill physical (compressed) bytes instead of logical. Here is how to cut storage cost.
Azure Synapse Analytics cost: dedicated pools, serverless, and Spark
Synapse bills dedicated SQL pools per DWU-hour, serverless SQL per TB scanned, and Spark pools per vCore-hour, plus data integration. Pausing dedicated pools and using serverless for ad-hoc queries are the big levers. Here is the breakdown.
Azure Data Factory cost: activity runs, data movement, and data flows
Data Factory bills orchestration per activity run, data movement per DIU-hour, and mapping data flows per vCore-hour, plus pipeline monitoring. Chatty pipelines and always-on data flow clusters are the usual overspend. Here is the breakdown.
Azure Databricks cost: DBUs on top of the underlying VMs
Databricks bills a DBU (Databricks Unit) rate per workload and tier, on top of the Azure VM cost of the cluster. Job clusters, Spot VMs, and autoscaling with autotermination are the big levers. Here is how the two-part model works.
GCP Dataflow cost: workers, memory, and the shuffle charge
Dataflow bills per vCPU-hour and GB-hour of worker time, plus a data-processed charge for Shuffle (batch) or Streaming Engine. Right-sizing workers and using the managed shuffle are the main levers. Here is how the model works.
GCP Dataproc cost: the surcharge on top of Compute Engine
Dataproc adds about $0.01 per vCPU-hour on top of the Compute Engine instances it runs, so the cluster costs more than the VMs alone. Ephemeral clusters, preemptible workers, and Dataproc Serverless are the main levers. Here is how to cut it.
AWS Glue cost optimization: DPU hours, crawlers, and the catalog
Glue bills about $0.44 per DPU-hour for jobs and crawlers, with a minimum billing per run, plus Data Catalog storage and request fees. Fewer, right-sized DPUs and less frequent crawling are the main levers. Here is the breakdown.
AWS EMR cost optimization: the surcharge, Spot, and Serverless
EMR adds a per-instance surcharge on top of EC2, so the cluster costs more than the instances alone. Spot for task nodes, right-sized core nodes, and EMR Serverless for bursty jobs are the main levers. Here is how to cut it.
AWS Athena cost optimization: you pay per terabyte scanned
Athena charges $5 per TB of data scanned, so cost is decided by how much data each query reads, not how often you query. Partitioning, columnar formats, and compression cut scans by an order of magnitude. Here is how.