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Databases · head to head

Databox vs DuckDB

Databox logo

Databox

Databases

KPI dashboards that pull from the tools you already run on

From
Free
Rated
-
Full reviewWebsite
DuckDB logo

DuckDB

Databases

MIT-licensed analytical SQL database that runs inside your process, with no server, no dependencies and one writer at a time.

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Databox data sources are the billing unit, so cost tracks the number of tools you connect rather than the value you get from them; DuckDB a database file accepts one read-write process at a time; other processes must open it read-only and will not see subsequent writes, so DuckDB cannot be the shared database behind several services.
  • They diverge on capability: Databox covers Pre-built dashboards, DuckDB covers In-process execution.
  • Prices and features above were last checked on 25 September 2026.

Where they differ

Only the attributes on which Databox and DuckDB actually diverge.

Attributes where Databox and DuckDB differ
AttributeDataboxDuckDB
Pricing modelsubscriptionopen-source
PlatformsWeb, Mobile, TvLinux, macOS, Windows, WebAssembly
CategoryUnknownDatabases
Founded20122019

Identical on both: starting price (Free), free tier (Yes), 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 Databox

  • Pre-built dashboards
  • Dashboard designer
  • Metric library
  • Goal tracking
  • Scorecards
  • Alerts
  • Scheduled reports
  • Client reporting

Only in DuckDB

  • In-process execution
  • Vectorised columnar engine
  • Direct file querying
  • Zero dependencies
  • Larger-than-memory queries
  • MIT licence
  • Postgres-flavoured SQL
  • Extension ecosystem

What people use each for

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

Databox

  • Watching marketing, sales and finance KPIs from separate SaaS tools on one shared dashboardnot DuckDB
  • Agencies reporting campaign performance to many clients without rebuilding a report per accountnot DuckDB
  • Putting a live KPI board on an office TV or a recurring email to a leadership teamnot DuckDB
  • Replacing a manually maintained spreadsheet that someone updates from tool exports each weeknot DuckDB
  • Tracking goals and getting alerted when a metric moves past a thresholdnot DuckDB

DuckDB

  • Transformation steps in a data pipeline that would otherwise need Spark, replaced by SQL over Parquet in a single processnot Databox
  • Analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptablenot Databox
  • Local exploration of files that are too large for a pandas dataframe but far too small to justify a warehousenot Databox
  • Continuous integration and testing of analytical SQL, where a real engine can run in the test process without provisioning anythingnot Databox

Where each one falls short

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

Databox

  • Data sources are the billing unit, so cost tracks the number of tools you connect rather than the value you get from them
  • The $71 Analyst plan is a single seat: adding even a second person means the $199 Core plan, a 2.8x jump
  • AI credits are metered monthly, from 50 on Free to 1,000 on Scale, so heavier AI use pushes you up a tier
  • Every published price assumes annual billing; monthly billing forfeits the advertised 20% saving
  • Free and Analyst plans sync daily and hourly respectively, so neither suits anything close to real-time monitoring
  • It is a dashboarding layer, not a warehouse: there is no transformation or modelling step for messy source data

DuckDB

  • A database file accepts one read-write process at a time; other processes must open it read-only and will not see subsequent writes, so DuckDB cannot be the shared database behind several services.
  • There is no network protocol, authentication or user management, so exposing it to remote clients means writing and securing your own service around it.
  • It is built for scans and aggregations, not for many small transactions, so a workload of high-frequency single-row inserts and updates performs badly compared with SQLite or Postgres.
  • Storage files are backwards compatible but not forwards compatible, so a file written by a newer version cannot be read by an older one and every consumer of a shared file must be upgraded together.
  • Query memory settings matter: some operations still need to hold significant state, so an under-configured memory limit turns a large join or a high-cardinality aggregation into a spill-heavy query or an out-of-memory failure rather than a slow success.

Pricing, plan by plan

Databox

Free
  • FreeFree
    • 3 data sources
    • 1 user
    • 50 AI credits per month
  • Analyst$71/month
    • 5 data sources
    • 1 user
    • 150 AI credits per month
  • Team - Core$199/month
    • 10 data sources
    • 3 users
    • 500 AI credits per month
  • Team - Scale$319/month
    • 30 data sources
    • 10 users
    • 1,000 AI credits per month

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Which should you pick?

Choose Databox if

  • You need pre-built dashboards.
  • You want to start without paying.
  • You work on Web, Mobile, Tv.
  • You also want dashboard designer.
Databox review

Choose DuckDB if

  • You need in-process execution.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, WebAssembly.
  • You also want vectorised columnar engine.
DuckDB review

Questions people ask

Is Databox or DuckDB better?
Neither clearly leads. Databox starts at Free and DuckDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Databox or DuckDB?
Databox starts at Free and DuckDB at Free.
Does Databox or DuckDB run on more platforms?
Databox runs on Web, Mobile, Tv. DuckDB runs on Linux, macOS, Windows, WebAssembly.
Can I use Databox for free?
Both have a free tier, so you can try either at no cost before committing.
What is Databox best used for?
Databox is most often used for watching marketing, sales and finance kpis from separate saas tools on one shared dashboard, agencies reporting campaign performance to many clients without rebuilding a report per account, putting a live kpi board on an office tv or a recurring email to a leadership team, replacing a manually maintained spreadsheet that someone updates from tool exports each week. Of those, watching marketing, sales and finance kpis from separate saas tools on one shared dashboard and agencies reporting campaign performance to many clients without rebuilding a report per account are not what DuckDB is typically brought in for.
What can Databox do that DuckDB cannot?
Databox covers Pre-built dashboards, Dashboard designer, Metric library, Goal tracking. DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies.

Answered from the vendors’ own pages

Databox: How much does Databox cost?

Databox has a free forever plan with 3 data sources and 1 user. Paid plans are Analyst at $71 per month, Team Core at $199 per month and Team Scale at $319 per month, with an Agency plan from $79 per month plus $20 client packs and a Custom tier on request. All prices are billed annually; monthly billing forfeits the 20% annual saving.

Source
DuckDB: Can multiple applications share one DuckDB database?

Not for writing. One process holds the database read-write; others may attach read-only and will not see later writes. Shared multi-writer access needs a different database or a table format with a catalogue.

Databox: Does Databox have a free plan or a free trial?

Both. The Free plan is free forever and covers 3 data sources, 1 user, 50 AI credits a month and daily syncing. Paid plans also offer a 14-day free trial with no credit card required.

Source
DuckDB: Is it a replacement for a data warehouse?

For single-node analytical workloads up to a few hundred gigabytes it very often is. It is not a replacement when many concurrent users need a shared, governed, always-on service.

Databox: How many users does each Databox plan include?

Free and Analyst are single-user. Team Core includes 3 users and Team Scale includes 10. The Agency and Custom plans include unlimited users.

Source
DuckDB: Do I have to load data into it?

No. It queries Parquet, CSV, JSON and Arrow in place, including on object storage. Its own storage format is optional and mainly useful when you want indexes, constraints and faster repeated access.

Databox: How many tools does Databox integrate with?

Databox connects to more than 130 tools, spreadsheets, databases and APIs, including HubSpot, Salesforce, Google Analytics, Google and Facebook Ads, Shopify, Stripe, QuickBooks, Google Sheets and custom API sources.

Source
DuckDB: What is MotherDuck's relationship to it?

MotherDuck is a separate company offering a managed and hybrid service built on the DuckDB engine. DuckDB itself remains MIT-licensed and independent of it, with the IP held by the DuckDB Foundation.

Databox: How often does Databox refresh its data?

The Free plan syncs daily. Analyst, Team Core, Team Scale, Agency and Custom plans all sync hourly.

Source
DuckDB: Is it suitable for OLTP?

No. It is designed for analytical scans. For transactional workloads with frequent small writes, SQLite or Postgres is the right tool.

Databox: Who makes Databox?

Databox, Inc., founded in 2012 by Davorin Gabrovec, who is now President and Chief Product Officer. Pete Caputa became CEO in 2017 after a decade at HubSpot. The company is headquartered in Boston, Massachusetts, with its product and engineering team based in Ptuj, Slovenia.

Source
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