databow: a Rust CLI to query any database with an ADBC driver

Reviewing the issues and PRs there provides a clue what to expect as this project matures.

ADBC: https://arrow.apache.org/docs/format/ADBC.html

Seems like a columnar version of ODBC, for OLAP instead of OLTP.

Sorry, just trying to understand. Why would I use this over duckdb. duckdb already has plugins for a lot of databases. Is the syntax the advantage?

My biggest pain point with using different cli to connect to different databases is that they all do things like listing tables differently.

Another nice feature one would want from such a program is of course auto complete.

This is excellent! I'm not a data engineer or SRE or whatever other commenters have mentioned. But part of my job is accessing data in various formats from various places, mostly offline. This in gonna be part of my toolset and I can pipe the output into other tools like nushell too.

Cool! But as a data engineer I don't know when I would ever use this. Getting data into a centralized place so it can be joined and queried easily is like prio 1 for any data team.

I'm sure SREs will really love me doing expensive adhoc queries against production postgres /s

I've yet to work in enterprises big enough to have multi cloud data warehouses though, maybe it's more useful in that setting?

Golang: https://github.com/xo/usql

Reviewing the issues and PRs there provides a clue what to expect as this project matures.

ADBC: https://arrow.apache.org/docs/format/ADBC.html

Seems like a columnar version of ODBC, for OLAP instead of OLTP.

Cool! But as a data engineer I don't know when I would ever use this. Getting data into a centralized place so it can be joined and queried easily is like prio 1 for any data team.

I'm sure SREs will really love me doing expensive adhoc queries against production postgres /s

I've yet to work in enterprises big enough to have multi cloud data warehouses though, maybe it's more useful in that setting?

As a consultant data engineer (ish), I think it has potential. You're right that any company doing data analytics is gonna be prioritizing a single source of truth and a unified platform, but each one will choose a different set of tools, which I'll have to learn, install, and even teach, for each new client. If I can use this to both explore AND implement stuff for clients regardless of their underlying database, that would be a pretty significant win.

Isn’t it useful for when you are getting things into a central DW?

E.g, you don’t need a million tools to connect to the million different application databases when inspecting sources as part of setting up pipelines.

My biggest pain point with using different cli to connect to different databases is that they all do things like listing tables differently.

Another nice feature one would want from such a program is of course auto complete.

Sorry, just trying to understand. Why would I use this over duckdb. duckdb already has plugins for a lot of databases. Is the syntax the advantage?

I find this to put my psql in a better place as a daily driver. Adding this to ~/.inputrc [1] will allow you to limit search on your entered text. Eg.

select (up arrow)

will loop through your psql history for commands that started with e.g., . The challenging part is in wide tables and or table with large data. Less is awkward usually so using pspg made it less awkward.

I tried also to with help of ai, to write a plugin for sublime that fits my flow. It worked well but I think I'm more used to psql.

[1]

~/.inputrc

$if psql "\e[A": history-search-backward "\e[B": history-search-forward $endif

edit: formatting

Yeah for me standardization is the big win. But not just output formatting but cli commands and a guarantee that they’re as past as possible given that all the connectors use ADBC

ClickHouse also supports a lot of data sources and has a local mode where you just use a single binary with local-only access.

Coincidentally, I wrote an article today on how I use it for similar scenarios. It can fetch from S3, multiple databases at once, and so on.

And you get all the benefits of a database when you need to join or postprocess data from multiple sources.

https://rushter.com/blog/clickhouse-data-processing/

It's more of a common database cli/shell which uses a well defined, and fast, ADBC protocol. You are basically freed from DuckDB's internal handling/runtime of query for various databases. Not to mention, this has vastly more supported databases.

With databow, the query still runs on the target database (unline duckdb), but you get one consistent CLI across different databases: connection profiles, output formats, history, scripting, and import/export behavior.

This is genuinely useful for humans (For example, I regularly juggle 6-7 different database, oltp, olap, search and key-value mixed), and even more useful for AI coding agents, because they don't have to learn and juggle a different CLI and set of flags for every database.

It’s going to have a very big hill to climb if it’s playing in a space where duckdb already has a hold. Duck has probably been my favourite technology find in the last few years. Awesome tech.

I’ll still check this out though.

I think the advantage is simplicity. Why connect first to duckdb and attach the db when you can query it directly with ADBC which is guaranteed to be fast

This is my question too

I find this to put my psql in a better place as a daily driver. Adding this to ~/.inputrc [1] will allow you to limit search on your entered text. Eg.

select (up arrow)

I tried also to with help of ai, to write a plugin for sublime that fits my flow. It worked well but I think I'm more used to psql.

[1]

~/.inputrc

$if psql "\e[A": history-search-backward "\e[B": history-search-forward $endif

edit: formatting

Isn’t it useful for when you are getting things into a central DW?

E.g, you don’t need a million tools to connect to the million different application databases when inspecting sources as part of setting up pipelines.

Thanks for sharing — this clears up a misconception I've had for a while.

That's a great point! "Speed to insight" feels more important than ever

Yeah for me standardization is the big win. But not just output formatting but cli commands and a guarantee that they’re as past as possible given that all the connectors use ADBC

ClickHouse also supports a lot of data sources and has a local mode where you just use a single binary with local-only access.

Coincidentally, I wrote an article today on how I use it for similar scenarios. It can fetch from S3, multiple databases at once, and so on.

And you get all the benefits of a database when you need to join or postprocess data from multiple sources.

https://rushter.com/blog/clickhouse-data-processing/

I think the advantage is simplicity. Why connect first to duckdb and attach the db when you can query it directly with ADBC which is guaranteed to be fast

You don’t need to connect to duckdb, it’s just a process that you spawn.

It’s going to have a very big hill to climb if it’s playing in a space where duckdb already has a hold. Duck has probably been my favourite technology find in the last few years. Awesome tech.

I’ll still check this out though.

Thanks for sharing — this clears up a misconception I've had for a while.

That's a great point! "Speed to insight" feels more important than ever

You don’t need to connect to duckdb, it’s just a process that you spawn.

This is my question too

TL;DR

databow is a new open source command-line tool for querying any database that has an ADBC driver. Built in Rust, databow gives you one fast, modern interface to the SQL systems across your entire data stack. Install it with uv tool install databow.

In a typical day, a data engineer might query a local embedded database, a distributed cloud data warehouse, and an enterprise relational database server—each with its own CLI. psql, mysql, snowsql, bq, sqlite3: different flags, different output formats, different quirks. Switching between them means relearning syntax and reformatting results. GUI tools exist, but they’re heavyweight and pull you out of the terminal.

What if one fast, modern CLI could connect to any database?

Meet databow

Today, we’re excited to introduce databow—an open source command-line tool for querying databases with ADBC (Arrow Database Connectivity).

databow is built in Rust for fast queries and a small footprint. It connects to any database that has an ADBC driver, giving you one unified interface for the SQL systems across your entire data stack.

What databow can do

Connect to 30+ databases

databow works with any database that has an ADBC driver. That includes:

Transactional databases: PostgreSQL, MySQL, MariaDB, SQLite, Oracle Database, Microsoft SQL Server, CockroachDB, YugabyteDB, TiDB
Analytical databases: DuckDB, ClickHouse, Snowflake, BigQuery, Databricks, Amazon Redshift, Teradata
Lakehouse engines: Trino, Dremio, StarRocks, Apache Doris
Time-series databases: InfluxDB, TimescaleDB, GreptimeDB

The list keeps growing as the ADBC ecosystem expands.

Run queries in an interactive SQL shell

databow provides a modern REPL with the features you’d expect:

$ databow --driver duckdb
> SELECT * FROM 'sales.parquet' LIMIT 5;
┌────────────┬─────────┬──────────┐
│ date       │ product │ revenue  │
├────────────┼─────────┼──────────┤
│ 2026-01-15 │ Widget  │ 1250.00  │
│ 2026-01-15 │ Gadget  │ 890.50   │
│ 2026-01-16 │ Widget  │ 1100.00  │
│ 2026-01-16 │ Gizmo   │ 2340.00  │
│ 2026-01-17 │ Gadget  │ 756.25   │
└────────────┴─────────┴──────────┘

Syntax highlighting with automatic light/dark theme detection
Multiline SQL input for complex queries
Clean, aligned tables with dynamic column widths
Command history for navigating previous queries

Export your results

Need to share your query results? Export directly to the format you need:

# Export to CSV
databow --driver postgresql --uri "postgres://localhost/analytics" \
  --query "SELECT * FROM monthly_report" \
  --output report.csv

# Export to JSON
databow --profile warehouse --query "SELECT * FROM users" \
  --output users.json

# Export to Arrow IPC
databow --profile prod-db --query "SELECT * FROM events" \
  --output events.arrow

Power your automations

databow isn’t just for interactive use. It’s designed to fit into scripts and pipelines:

# Execute a query directly
databow --driver duckdb --uri warehouse.db --query "SELECT count(*) FROM logs WHERE level = 'ERROR'"

# Read from a SQL file
databow --driver postgresql --uri "postgres://localhost/analytics" \
  --file daily_metrics.sql --output metrics.csv

# Pipe queries from stdin
echo "SELECT version()" | databow --driver postgresql --uri "$DATABASE_URL"

Load connection details from profiles

Tired of typing long database connection strings? Save your configurations in ADBC connection profiles and refer to them by name:

# Use a saved profile
databow --profile production-warehouse --query "SELECT * FROM orders"

Why ADBC

databow is built on ADBC—the Arrow Database Connectivity standard from the Apache Arrow project. ADBC provides a vendor-neutral API for database access, similar to what JDBC and ODBC do for legacy connectivity. But ADBC is designed from the ground up to transfer data in the Apache Arrow format. That means:

Efficient data transfer: Results come back in Arrow’s columnar format, and when the database speaks Arrow natively, that means no row-by-row serialization overhead at all.
Consistent behavior: The same API works across databases.
Growing ecosystem: As more databases add ADBC drivers, databow automatically supports them.

By building on ADBC, databow benefits from the work of the entire Arrow community. When a new database releases an ADBC driver, databow users get access immediately.

Get started

databow ships as a single binary. Install it with uv or Cargo:

# Recommended: install with uv
uv tool install databow

# Alternative: install with Cargo
cargo install databow

Then install the ADBC driver for your database using dbc, the command-line tool for installing and managing ADBC drivers. For example, to install the ADBC driver for DuckDB:

dbc install duckdb

Then start querying:

databow --driver duckdb

Roadmap

We’re actively working on new features to make databow even more powerful:

Dot commands: Interactive commands for quick configuration and exploration
More export formats: Support for writing results to Parquet and other file types
Result set truncation: Configurable limits for large result sets to keep your terminal responsive
Data type display: Show column data types alongside query results for better schema visibility

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