ADBC: Arrow Database Connectivity#
Full Documentation on ADBC can be found at https://arrow.apache.org/adbc/.
Rationale#
The Arrow ecosystem lacks standard database interfaces built around Arrow data, especially for efficiently fetching large datasets (i.e. with minimal or no serialization and copying). Without a common API, the end result is a mix of custom protocols (e.g. BigQuery, Snowflake) and adapters (e.g. Turbodbc) scattered across languages. Consumers must laboriously wrap individual systems (as DBI is contemplating and Trino does with connectors).
ADBC aims to provide a minimal database client API standard, based on Arrow, for C, Go, and Java (with bindings for other languages). Applications code to this API standard (in much the same way as they would with JDBC or ODBC), but fetch result sets in Arrow format (e.g. via the C Data Interface). They then link to an implementation of the standard: either directly to a vendor-supplied driver for a particular database, or to a driver manager that abstracts across multiple drivers. Drivers implement the standard using a database-specific API, such as Flight SQL.
Goals#
Provide a cross-language, Arrow-based API to standardize how clients submit queries to and fetch Arrow data from databases.
Support both SQL dialects and the emergent Substrait standard.
Support explicitly partitioned/distributed result sets to work better with contemporary distributed systems.
Allow for a variety of implementations to maximize reach.
Non-goals#
Replacing JDBC/ODBC in all use cases, particularly OLTP use cases.
Requiring or enshrining a particular database protocol for the Arrow ecosystem.
Example use cases#
A C or C++ application wishes to retrieve bulk data from a Postgres database for further analysis. The application is compiled against the ADBC header, and executes queries via the ADBC APIs. The application is linked against the ADBC libpq driver. At runtime, the driver submits queries to the database via the Postgres client libraries, and retrieves row-oriented results, which it then converts to Arrow format before returning them to the application.
If the application wishes to retrieve data from a database supporting Flight SQL instead, it would link against the ADBC Flight SQL driver. At runtime, the driver would submit queries via Flight SQL and get back Arrow data, which is then passed unchanged and uncopied to the application. (The application may have to edit the SQL queries, as ADBC does not translate between SQL dialects.)
If the application wishes to work with multiple databases, it would link against the ADBC driver manager, and specify the desired driver at runtime. The driver manager would pass on API calls to the correct driver, which handles the request.
ADBC API Standard 1.0.0#
ADBC is a language-specific set of interface definitions that can be implemented directly by a vendor-specific “driver” or a vendor-neutral “driver manager”.
Version 1.0.0 of the standard corresponds to tag adbc-1.0.0 of the
repository apache/arrow-adbc, which is commit
f044edf5256abfb4c091b0ad2acc73afea2c93c0. Note that is separate
from releases of the actual implementations.
See the language-specific pages for details:
Updating this specification#
ADBC is versioned separately from the core Arrow project. The API standard and components (driver manager, drivers) are also versioned separately, but both follow semantic versioning.
For example: components may make backwards-compatible releases as 1.0.0, 1.0.1, 1.1.0, 1.2.0, etc. They may release backwards-incompatible versions such as 2.0.0, but which still implement the API standard version 1.0.0.
Similarly, this documentation describes the ADBC API standard version 1.0.0. If/when an ABI-compatible revision is made (e.g. new standard options are defined), the next version would be 1.1.0. If incompatible changes are made (e.g. new API functions), the next version would be 2.0.0.
Related work#
In the initial proposal, a survey of existing solutions and systems was included, which is reproduced below for context, though note the descriptions are only kept up-to-date on a best-effort basis.
Comparison with Arrow Flight SQL#
Flight SQL is a client-server protocol oriented at database developers. By implementing Flight SQL, a database can support clients that use ADBC, JDBC, and ODBC.
ADBC is an API specification oriented at database clients. By coding to ADBC, an application can get Arrow data from a variety of databases that use different client technologies underneath.
Hence, the two projects complement each other. While Flight SQL provides a client that can be used directly, we expect applications would prefer to use ADBC instead of tying themselves to a particular database.
Comparison with JDBC/ODBC#
JDBC is a row-based API, so bridging JDBC to Arrow is hard to do efficiently.
ODBC provides support for bulk data with block cursors, and Turbodbc demonstrates that a performant Arrow-based API can be built on top. However, it is still an awkward fit for Arrow:
Nulls (‘indicator’ values) are represented as integers, requiring conversion.
Result buffers are caller-allocated. This can force unnecessarily copying data. ADBC uses the C Data Interface instead, eliminating copies when possible (e.g. if the driver uses Flight SQL).
Some data types are represented differently, and require conversion. SQL_C_BINARY can sidestep this for drivers and applications that cooperate, but then applications would have to treat Arrow-based and non-Arrow-based data sources differently.
Strings must be null-terminated, which would require a copy into an Arrow array, or require that the application handle null terminated strings in an array.
It is implementation-defined whether strings may have embedded nulls, but Arrow specifies UTF-8 strings for which 0x00 is a valid byte.
Because buffers are caller-allocated, the driver and application must cooperate to handle large strings; the driver must truncate the value, and the application can try to fetch the value again.
ODBC uses length buffers rather than offsets, requiring another conversion to/from Arrow string arrays.
Hence, we think just extending ODBC is insufficient to meet the goals of ADBC. ODBC will always be valuable for wider database support, and providing an Arrow-based API on top of ODBC is useful. ADBC would allow implementing/optimizing this conversion in a common library, provide a simpler interface for consumers, and would provide an API that Arrow-native or otherwise columnar systems can implement to bypass this wrapper.
ADBC, JDBC, and ODBC are database-agnostic. They define the API that the application uses, but not how that API is implemented, instead deferring to drivers to fulfill requests using the protocol of their choice. JDBC and (generally) ODBC offer results in a row-oriented format, while ADBC offers columnar Arrow data.#
Protocols/libraries like libpq (Postgres) and TDS (SQL Server) are database-specific and row-oriented. Multiple databases may implement the same protocol to try to reuse each other’s work, e.g. several databases implement the Postgres wire protocol to benefit from its driver implementations. But the protocol itself was not designed with multiple databases in mind, nor are the protocols generally meant to be used directly by applications.
Some database-specific protocols are Arrow-native, like those of BigQuery and ClickHouse. Flight SQL additionally is meant to be database-agnostic, but it defines both the client-facing API and the underlying protocol, so it’s hard for applications to use it as the API for databases that don’t already implement Flight SQL.
Existing database client APIs#
- Arrow Flight SQL
A standard building on top of Arrow Flight, defining how to use Flight to talk to databases, retrieve metadata, execute queries, and so on. Provides a single client in C++ and Java language that talks to any database servers implementing the protocol. Models its API surface (though not API design) after JDBC and ODBC.
- DBI for R
An R package/ecosystem of packages for database access. Provides a single interface with “backends” for specific databases. While row-oriented, integration with Arrow is under consideration, including a sketch of effectively the same idea as ADBC.
- JDBC
A Java library for database access, providing row-based APIs. Provides a single interface with drivers for specific databases.
- ODBC
A language-agnostic standard from the ISO/IEC for database access, associated with Microsoft. Feature-wise, it is similar to JDBC (and indeed JDBC can wrap ODBC drivers), but it offers columnar data support through fetching buffers of column values. (See above for caveats.) Provides a single C interface with drivers for specific databases.
- PEP 249 (DBAPI 2.0)
A Python standard for database access providing row-based APIs. Not a singular package, but rather a set of interfaces that packages implement.
Existing libraries#
These are libraries which either 1) implement columnar data access for a particular system; or 2) could be used to implement such access.
- Arrow Flight
An RPC framework optimized for transferring Arrow record batches, with application-specific extension points but without any higher level semantics.
- Arrow JDBC
A Java submodule, part of Arrow/Java, that uses the JDBC API to produce Arrow data. Internally, it can read data only row-at-a-time.
- arrow-odbc
A Rust community project that uses the ODBC API to produce Arrow data, using ODBC’s buffer-based API to perform bulk copies. (See also: Turbodbc.)
- Arrowdantic
Python bindings for an implementation of ODBC<>Arrow in Rust.
- pgeon
A client that manually parses the Postgres wire format and produces Arrow data, bypassing JDBC/ODBC. While it attempts to optimize this case, the Postgres wire protocol is still row-oriented.
- Turbodbc
A set of Python ODBC bindings, implementing PEP 249, that also provides APIs to fetch data as Arrow batches, optimizing the conversion internally.
Papers#
Raasveldt, Mark, and Hannes Mühleisen. “Don’t Hold My Data Hostage - A Case for Client Protocol Redesign”. In Proceedings of the VLDB Endowment, 1022–1033, 2017.