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Databases · head to head

BigQuery vs Periscope Data

BigQuery logo

BigQuery

Databases

Google Cloud's serverless analytical warehouse, billed either by bytes scanned per query or by reserved compute slots.

From
Free
Rated
-
Full reviewWebsite
Periscope Data logo

Periscope Data

Business Intelligence

SQL and Python analytics platform

From
$1000/month
Rated
-
Full reviewWebsite

The short version

  • Only BigQuery has a free tier, so it costs nothing to try first.
  • Each has a real cost: BigQuery on-demand billing charges for bytes read from every column a query references, so an unqualified select or a missing partition filter turns a routine query into a large bill, and the cost is discovered after the fact rather than at review time.; Periscope Data the periscopedata.com domain now redirects to sisense.com, so Periscope Data is no longer sold as a standalone product
  • They diverge on capability: BigQuery covers Serverless compute, Periscope Data covers SQL Editor.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which BigQuery and Periscope Data actually diverge.

Attributes where BigQuery and Periscope Data differ
AttributeBigQueryPeriscope Data
Starting priceFree$1000/month
Pricing modelusage-basedsubscription
Free tierYesNo
PlatformsWeb, Cloud APIWeb, Cloud
CategoryDatabasesBusiness Intelligence
Founded20082012

Identical on both: user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in BigQuery

  • Serverless compute
  • Separation of storage and compute
  • Two pricing models
  • Partitioning and clustering
  • Materialised views
  • BigQuery ML
  • Storage Write API
  • BI Engine

Only in Periscope Data

  • SQL Editor
  • Python/R Integration
  • Version Control
  • Caching
  • Dashboards
  • Redshift
  • BigQuery
  • Snowflake

What people use each for

The jobs each tool is most often brought in to do.

BigQuery

  • A warehouse for an organisation already on Google Cloud, where identity, logging and billing are consolidated in the same placenot Periscope Data
  • Bursty analytical workloads with long idle periods, where paying per query beats keeping a cluster runningnot Periscope Data
  • Event and clickstream analytics ingested continuously through the Storage Write API and queried without a load windownot Periscope Data
  • Analytics teams with no infrastructure staff, where the absence of anything to tune or patch is worth more than dialect portabilitynot Periscope Data

Periscope Data

  • SQL-based analytics and dashboards over a data warehousenot BigQuery
  • Python and R analysis alongside SQL in one workflownot BigQuery
  • Shared dashboards for data teamsnot BigQuery

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

BigQuery

  • On-demand billing charges for bytes read from every column a query references, so an unqualified select or a missing partition filter turns a routine query into a large bill, and the cost is discovered after the fact rather than at review time.
  • There is no way to join tables that live in different regions, so a data estate split across regions for residency reasons has to be reconciled with copies and the storage and transfer that implies.
  • It is not built for point lookups; retrieving a single row has latency measured in hundreds of milliseconds or more, so BigQuery cannot serve an application's read path and always needs a second store in front of it.
  • Frequent small mutations run into DML concurrency limits and the cost of rewriting storage blocks, so a workload that updates individual rows continuously behaves badly compared with an append-only design.
  • The compute exists only inside Google Cloud, so while tables can be exported, the accumulated GoogleSQL, scheduled queries, authorised views, ML models and IAM structure do not move, and switching warehouses is a rewrite of the analytical layer.

Periscope Data

  • The periscopedata.com domain now redirects to sisense.com, so Periscope Data is no longer sold as a standalone product
  • No Periscope Data pricing, plan or seat rate remains published at the original domain
  • Buyers must now purchase through Sisense, whose own pricing is not published as a rate card

Pricing, plan by plan

BigQuery

Free
  • Free TierFree
    • 1TB queries/month
    • 10GB storage/month
    • Standard support
  • On-demand$6.25/TB
    • Pay per query
    • Pay per storage
    • All features

Periscope Data

$1000/month
  • Team$1000/month
    • SQL Analytics
    • Python/R
    • Dashboards
  • EnterpriseFree
    • Advanced Features
    • Custom Integrations
    • Premium Support

Which should you pick?

Choose BigQuery if

  • You need serverless compute.
  • You want to start without paying.
  • You work on Web, Cloud API.
  • You also want separation of storage and compute.
BigQuery review

Choose Periscope Data if

  • You need sql editor.
  • You work on Web, Cloud.
  • You also want python/r integration.
Periscope Data review

Questions people ask

Is BigQuery or Periscope Data better?
Neither clearly leads. BigQuery starts at Free and Periscope Data at $1000/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigQuery or Periscope Data?
BigQuery has a free tier; the other does not. Paid plans start at Free for BigQuery and $1000/month for Periscope Data.
Does BigQuery or Periscope Data run on more platforms?
BigQuery runs on Web, Cloud API. Periscope Data runs on Web, Cloud.
Can I use BigQuery for free?
Yes. BigQuery has a free tier, so you can try it without paying. Periscope Data starts at $1000/month.
What is BigQuery best used for?
BigQuery is most often used for a warehouse for an organisation already on google cloud, where identity, logging and billing are consolidated in the same place, bursty analytical workloads with long idle periods, where paying per query beats keeping a cluster running, event and clickstream analytics ingested continuously through the storage write api and queried without a load window, analytics teams with no infrastructure staff, where the absence of anything to tune or patch is worth more than dialect portability. Of those, a warehouse for an organisation already on google cloud, where identity, logging and billing are consolidated in the same place and bursty analytical workloads with long idle periods, where paying per query beats keeping a cluster running are not what Periscope Data is typically brought in for.
What can BigQuery do that Periscope Data cannot?
BigQuery covers Serverless compute, Separation of storage and compute, Two pricing models, Partitioning and clustering. Periscope Data covers SQL Editor, Python/R Integration, Version Control, Caching.

Answered from the vendors’ own pages

BigQuery: How is BigQuery actually billed?

Storage is billed separately from compute. Compute is either on-demand, priced by the bytes a query reads from the referenced columns, or capacity-based, where you reserve autoscaling slots. Most cost surprises come from on-demand queries that scan more than expected.

Periscope Data: Does Sisense offer a free trial?

Yes. Sisense offers a free trial of their Self-Serve plan. You can try features like data warehouse connectivity, built-in AI for natural-language queries, auto-narratives, and customer assistant features.

Source
BigQuery: How do I control query cost?

Partition and cluster tables so queries prune data, select only the columns needed, use materialised views for repeated aggregations, and set maximum bytes billed on queries so a runaway scan fails instead of billing.

Periscope Data: What is the difference between Sisense Self-Serve and Enterprise plans?

The Self-Serve plan is for startups and teams and includes basic connectivity and AI features with iframe embedding. The Enterprise plan is for regulated industries and includes multi-tenant architecture, HIPAA readiness, column-level security, single sign-on, on-premise deployment options, 99.99% SLA, and 30-day backups.

Source
BigQuery: Can I use it without being on Google Cloud?

The service only runs on Google Cloud. BigQuery Omni can query data held in S3 or Azure storage, but the compute is still Google's and the account relationship is still with Google.

Periscope Data: How do I access the Sisense Enterprise plan?

The Enterprise plan requires contacting Sisense for a demo and custom quote. There is no self-service signup for this tier.

Source
BigQuery: Is it suitable for serving application queries?

No. Latency for single-row reads is far too high. BigQuery is an analytical warehouse and application read paths need a transactional database or a cache in front of it.

BigQuery: When should I move from on-demand to capacity pricing?

When on-demand spend becomes both large and predictable, or when unpredictable spend is a bigger problem than query queueing. The switch trades a variable bill for a fixed one plus contention between workloads.

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