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Databases · head to head

DuckDB vs Equals

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
Equals logo

Equals

Spreadsheets

A real spreadsheet with SQL result sets landing in its cells, now sold only on annual contracts starting at 24,000 USD

From
$24000/year
Rated
-
Full reviewWebsite

The short version

  • Only DuckDB has a free tier, so it costs nothing to try first.
  • Each has a real cost: 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.; Equals the price list now starts at 24,000 USD a year with no monthly billing and no self-serve signup, having offered a free plan in 2023 and 39 USD per seat in 2024, so any team that evaluated it previously is looking at a different product commercially.
  • They diverge on capability: DuckDB covers In-process execution, Equals covers Connected sheets.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which DuckDB and Equals actually diverge.

Attributes where DuckDB and Equals differ
AttributeDuckDBEquals
Starting priceFree$24000/year
Pricing modelopen-sourcePer year by connector count and refresh frequency
Free tierYesNo
PlatformsLinux, macOS, Windows, WebAssemblyWeb, API
CategoryDatabasesSpreadsheets
Founded2019Unknown

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 DuckDB

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

Only in Equals

  • Connected sheets
  • Real spreadsheet mechanics
  • Cell references into SQL
  • Equals Warehouse
  • Views
  • Writeback

What people use each for

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

DuckDB

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

Equals

  • A revenue operations team that wants software metrics computed in a spreadsheet rather than defined in a BI semantic layernot DuckDB
  • Analysts who need a SQL result and manual assumptions in the same file, with the assumptions visible as cellsnot DuckDB
  • Joining Stripe, Salesforce and a production database without building a warehouse and pipeline firstnot DuckDB
  • Distributing a recurring numbers pack to Slack, email or a wall display without rebuilding it as a dashboardnot DuckDB

Where each one falls short

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

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.

Equals

  • The price list now starts at 24,000 USD a year with no monthly billing and no self-serve signup, having offered a free plan in 2023 and 39 USD per seat in 2024, so any team that evaluated it previously is looking at a different product commercially.
  • Your data is copied out of your infrastructure by design, into a Snowflake warehouse that Equals operates, with Fivetran holding non-SQL source data in transit, and no self-hosted or bring-your-own-warehouse option is documented.
  • The financial function category contains only IRR, NPV and PMT, with no XIRR, XNPV, FV, PV, RATE or NPER, and there is no LAMBDA, LET, OFFSET or INDIRECT, so a substantial class of existing spreadsheet models cannot be ported without rework.
  • No documentation of importing or exporting Excel files exists anywhere in the docs index; the supported file sources are CSV and Google Sheets and the only documented export is dashboards as PDF, which is a notable gap for a product positioning itself as a successor to Excel.
  • Data freshness is a pricing lever rather than a setting, at six hours on Essential, one hour on Business and fifteen minutes on Enterprise, and the feature that removes row limits is itself gated above the entry tier, so the Essential row ceiling is neither published nor unlimited.

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Equals

$24000/year
  • Essential$24000/year
    • Unlimited viewers and unlimited editors
    • 3 connectors
    • Data sync every 6 hours
  • Business$36000/year
    • Unlimited viewers and unlimited editors
    • 5 connectors or a warehouse connection
    • Data sync every hour
  • Enterprise$60000/year
    • Unlimited viewers and unlimited editors
    • Unlimited connectors or a warehouse connection
    • Data sync every 15 minutes
  • Connector add-ons$199/month
    • 199 USD per month for each additional database or import script connector
    • 699 USD per month for each additional connector of any other type
    • Available on Business and Enterprise

Which should you pick?

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

Choose Equals if

  • You need connected sheets.
  • You work on Web, API.
  • You also want real spreadsheet mechanics.
Equals review

Questions people ask

Is DuckDB or Equals better?
Neither clearly leads. DuckDB starts at Free and Equals at $24000/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Equals?
DuckDB has a free tier; the other does not. Paid plans start at Free for DuckDB and $24000/year for Equals.
Does DuckDB or Equals run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Equals runs on Web, API.
Can I use DuckDB for free?
Yes. DuckDB has a free tier, so you can try it without paying. Equals starts at $24000/year.
What is DuckDB best used for?
DuckDB is most often used for transformation steps in a data pipeline that would otherwise need spark, replaced by sql over parquet in a single process, analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptable, local exploration of files that are too large for a pandas dataframe but far too small to justify a warehouse, continuous integration and testing of analytical sql, where a real engine can run in the test process without provisioning anything. Of those, transformation steps in a data pipeline that would otherwise need spark, replaced by sql over parquet in a single process and analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptable are not what Equals is typically brought in for.
What can DuckDB do that Equals cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Equals covers Connected sheets, Real spreadsheet mechanics, Cell references into SQL, Equals Warehouse.

Answered from the vendors’ own pages

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.

Equals: Is it a real spreadsheet or a modelling tool with a grid?

A real spreadsheet. A1 references, absolute reference locking, pivot tables and spilling array formulas all work, and SQL results land in ranges that ordinary cells reference.

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.

Equals: What does it actually cost?

24,000 USD a year for Essential, 36,000 for Business and 60,000 for Enterprise, billed annually. There is no monthly option and no self-serve signup; the trial is negotiated per customer.

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.

Equals: Are seats charged?

No. Viewers and editors are unlimited on every plan. The meters are connector count, refresh frequency and AI spend, with additional connectors at 199 or 699 USD a month.

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.

Equals: Does my data stay in my own warehouse?

No. Connecting more than one source syncs data into a Snowflake warehouse that Equals runs, and non-SQL sources pass through Fivetran. There is no documented self-hosted option.

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.

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