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Databases · head to head

DuckDB vs Jaeger

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
Jaeger logo

Jaeger

Cloud

Open-source end-to-end distributed tracing

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.; Jaeger tracing is only as good as the instrumentation, and partial instrumentation produces misleading gaps
  • They diverge on capability: DuckDB covers In-process execution, Jaeger covers Distributed trace search.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and Jaeger actually diverge.

Attributes where DuckDB and Jaeger differ
AttributeDuckDBJaeger
Pricing modelopen-sourceOpen source, no licence fee
PlatformsLinux, macOS, Windows, WebAssemblyLinux, Kubernetes, Docker
CategoryDatabasesCloud
Founded2019Unknown

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 Jaeger

  • Distributed trace search
  • Dependency graph
  • Adaptive sampling
  • Pluggable storage

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

Jaeger

  • Finding which service in a request path causes the latencynot DuckDB
  • Understanding real service dependencies rather than the diagram on the wikinot DuckDB
  • Debugging failures that only appear under production traffic patternsnot 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.

Jaeger

  • Tracing is only as good as the instrumentation, and partial instrumentation produces misleading gaps
  • Storage is the real operational cost: high-volume tracing on Elasticsearch or Cassandra is a cluster to run and pay for
  • Traces alone, without correlated metrics and logs, leave you switching between tools during an incident

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Jaeger

Free
  • JaegerFree
    • Full functionality
    • No usage limits
    • Community support

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 Jaeger if

  • You need distributed trace search.
  • You want to start without paying.
  • You work on Linux, Kubernetes, Docker.
  • You also want dependency graph.
Jaeger review

Questions people ask

Is DuckDB or Jaeger better?
Neither clearly leads. DuckDB starts at Free and Jaeger at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Jaeger?
DuckDB starts at Free and Jaeger at Free.
Does DuckDB or Jaeger run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Jaeger runs on Linux, Kubernetes, Docker.
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 Jaeger is typically brought in for.
What can DuckDB do that Jaeger cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Jaeger covers Distributed trace search, Dependency graph, Adaptive sampling, Pluggable storage.

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.

Jaeger: Is Jaeger free?

Yes, open source and CNCF-graduated. Costs are the storage backend you run.

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.

Jaeger: Do I use Jaeger or OpenTelemetry?

Both, usually. Instrument with OpenTelemetry and use Jaeger to store and query the traces.

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.

Jaeger: Does Jaeger handle metrics and logs?

No. It is a tracing system. Metrics and logs need Prometheus, Loki or an equivalent.

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.

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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