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Databases · head to head

DuckDB vs Microsoft SQL Server

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
-
Microsoft SQL Server logo

Microsoft SQL Server

Databases

Enterprise-grade relational database management system

From
Free
Rated
-

The short version

  • 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.; Microsoft SQL Server licensing and on-premises deployment costs are high compared to open-source alternatives, with Enterprise Edition exceeding $60,000 for minimum core requirements
  • They diverge on capability: DuckDB covers In-process execution, Microsoft SQL Server covers T-SQL.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and Microsoft SQL Server actually diverge.

Attributes where DuckDB and Microsoft SQL Server differ
AttributeDuckDBMicrosoft SQL Server
Pricing modelopen-sourceUnknown
PlatformsLinux, macOS, Windows, WebAssemblyWindows Server, Linux (RHEL, SUSE, Ubuntu), Docker, Azure
Founded20191989

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).

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 Microsoft SQL Server

  • T-SQL
  • ACID Compliance
  • Advanced Security
  • In-memory OLTP
  • Columnstore Indexes
  • Always On Availability
  • Machine Learning Services
  • Azure

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 Microsoft SQL Server
  • Analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptablenot Microsoft SQL Server
  • Local exploration of files that are too large for a pandas dataframe but far too small to justify a warehousenot Microsoft SQL Server
  • Continuous integration and testing of analytical SQL, where a real engine can run in the test process without provisioning anythingnot Microsoft SQL Server

Microsoft SQL Server

  • Transaction processingnot DuckDB
  • Data storagenot DuckDB
  • Application backendnot DuckDB
  • Reportingnot DuckDB
  • Data analyticsnot 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.

Microsoft SQL Server

  • Licensing and on-premises deployment costs are high compared to open-source alternatives, with Enterprise Edition exceeding $60,000 for minimum core requirements
  • Performance monitoring toolset is insufficient for hybrid cloud environments requiring real-time analytics across multiple deployment types
  • Heavy I/O resource consumption can saturate disk volumes and degrade performance when processing large transaction workloads
  • Always On availability groups with up to 8 secondary replicas are limited to Enterprise edition only; Standard supports only basic availability groups with 2 replicas
  • CPU and memory scaling is capped at 4 sockets or 32 cores on Standard edition, limiting deployments requiring higher compute capacity

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Microsoft SQL Server

Free
  • ExpressFree
    • 4 cores maximum
    • 1.4 GB memory per instance
    • 50 GB database size limit
  • DeveloperFree
    • All Enterprise features
    • Non-production use only
  • Standard$3945/per 2-core pack
    • 32 core maximum per instance
    • 256 GB buffer pool memory
    • Basic availability groups with 2 replicas
  • Enterprise$15123/per 2-core pack
    • Unlimited scaling
    • Always On with up to 8 secondaries
    • Advanced security and HA features

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.

Choose Microsoft SQL Server if

  • You need t-sql.
  • You want to start without paying.
  • You work on Windows Server, Linux (RHEL, SUSE, Ubuntu), Docker, Azure.
  • You also want acid compliance.

Questions people ask

Is DuckDB or Microsoft SQL Server better?
Neither clearly leads. DuckDB starts at Free and Microsoft SQL Server at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Microsoft SQL Server?
DuckDB starts at Free and Microsoft SQL Server at Free.
Does DuckDB or Microsoft SQL Server run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Microsoft SQL Server runs on Windows Server, Linux (RHEL, SUSE, Ubuntu), Docker, Azure.
Can I use DuckDB for free?
Both have a free tier, so you can try either at no cost before committing.
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 Microsoft SQL Server is typically brought in for.
What can DuckDB do that Microsoft SQL Server cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Microsoft SQL Server covers T-SQL, ACID Compliance, Advanced Security, In-memory OLTP.

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.

Microsoft SQL Server: What is the pricing model for SQL Server?

SQL Server uses core-based licensing with per-2-core pack pricing. Enterprise Edition costs approximately $15,123 per 2-core pack (minimum 8 cores). Standard Edition costs approximately $3,945 per 2-core pack. Developer and Express editions are free. Software Assurance adds 25-35% annually for upgrades and support.

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.

Microsoft SQL Server: Does SQL Server run on Linux?

Yes. SQL Server 2017 and later run on Linux (Red Hat Enterprise Linux, SUSE Linux Enterprise Server, Ubuntu), Docker containers, and Windows with feature parity including Always On availability groups, Active Directory authentication, and encryption.

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.

Microsoft SQL Server: Is there a free edition of SQL Server?

Yes. SQL Server Express is free and includes all functionality of Enterprise edition for development and testing, with limits of 4 cores, 1,410 MB memory per instance, and 50 GB per database. Developer edition is also free for non-production use.

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.

Microsoft SQL Server: Can SQL Server be deployed offline?

Yes. SQL Server can be installed from offline media on machines without internet access. Microsoft provides complete offline installation packages for SQL Server, SSMS, and supporting components, making deployment in isolated or air-gapped environments feasible.

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.

Microsoft SQL Server: What high availability options does SQL Server provide?

SQL Server offers Always On availability groups (Enterprise only), Always On failover cluster instances, database mirroring, log shipping, and for disaster recovery, failover servers in Azure and Accelerated Database Recovery for faster recovery after failures.

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