Softwr

Databases · head to head

DuckDB vs InfluxDB

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
InfluxDB logo

InfluxDB

Logging

Purpose-built time series database for metrics and events

From
Free
Rated
-
Full reviewWebsite

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.; InfluxDB high-cardinality data causes memory pressure and performance degradation
  • They diverge on capability: DuckDB covers In-process execution, InfluxDB covers Time-series Storage.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and InfluxDB actually diverge.

Attributes where DuckDB and InfluxDB differ
AttributeDuckDBInfluxDB
Pricing modelopen-sourceUnknown
PlatformsLinux, macOS, Windows, WebAssemblyCloud, Docker, Linux, macOS, Windows, AWS, Google Cloud, Azure
CategoryDatabasesLogging
Founded20192012

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 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 InfluxDB

  • Time-series Storage
  • Flux Query Language
  • High Write Throughput
  • Data Compression
  • Retention Policies
  • Continuous Queries
  • Built-in Dashboards
  • Telegraf

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

InfluxDB

  • Monitoringnot DuckDB
  • IoT datanot DuckDB
  • Financial datanot DuckDB
  • Log analyticsnot DuckDB
  • Observabilitynot 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.

InfluxDB

  • High-cardinality data causes memory pressure and performance degradation
  • No support for joins or transactions like relational databases
  • Queries limited to 72-hour window in InfluxDB 3 OSS Core
  • Clustering and authentication features absent from community version

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

InfluxDB

Free
  • Cloud Serverless FreeFree
    • 5 MB writes per 5 minutes
    • 300 MB queries per 5 minutes
    • 30 day retention
  • Cloud Serverless Usage-Based$undefined/mo
    • 0.0025 USD per MB ingested
    • 0.012 USD per 100 queries
    • 0.002 USD per GB-hour storage

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 InfluxDB if

  • You need time-series storage.
  • You want to start without paying.
  • You work on Cloud, Docker, Linux, macOS, Windows, AWS, Google Cloud, Azure.
  • You also want flux query language.
InfluxDB review

Questions people ask

Is DuckDB or InfluxDB better?
Neither clearly leads. DuckDB starts at Free and InfluxDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or InfluxDB?
DuckDB starts at Free and InfluxDB at Free.
Does DuckDB or InfluxDB run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. InfluxDB runs on Cloud, Docker, Linux, macOS, Windows, AWS, Google Cloud, 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 InfluxDB is typically brought in for.
What can DuckDB do that InfluxDB cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. InfluxDB covers Time-series Storage, Flux Query Language, High Write Throughput, Data Compression.

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.

InfluxDB: Is there a free tier and what are the limits?

InfluxDB 3 Core OSS is free forever for local development and prototyping. Cloud Serverless free tier includes 5 MB writes per 5 minutes, 300 MB queries per 5 minutes, 30 day retention, and 2 databases.

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.

InfluxDB: Can I self-host InfluxDB?

Yes, InfluxDB 3 Core is fully open source and can be self-hosted with no license required. InfluxDB 3 Enterprise is self-managed and includes a 30-day free trial.

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.

InfluxDB: What are the series cardinality limitations?

InfluxDB is sensitive to high-cardinality data. High cardinality increases RAM usage and can trigger out-of-memory errors, making it unsuitable for some workloads with many unique tag combinations.

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.

InfluxDB: Does InfluxDB support SQL queries?

InfluxDB has limited SQL support. Full SQL is available in InfluxDB 3, but earlier versions support only specific SQL commands and use InfluxQL as the primary query language.

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.

InfluxDB: Can I export my data from InfluxDB?

Yes, data can be exported from InfluxDB using query results. However, the process and supported formats depend on the version and deployment type you are using.

Source
Share

Related pages

More on DuckDB

More on InfluxDB

Keep looking

Other head to heads