![]() ![]() To connect to your running Flight SQL server via ADBC in Python follow these steps:ġ- Ensure you have Python 3. To learn more about the advantages of using ADBC with Flight SQL, you can read our blog post here. For more details, you can see our intro to ADBC blog post. These tools are tailored for high-performance interactions with databases, potentially accelerating the backup and restore processes compared to general data transfer methods. Unlike JDBC, ADBC uses Arrow data everywhere, avoiding data conversions. The native backup and restore differs from the standard DBeaver Data Transfer feature by focusing on creating and applying database backups using specialized utilities. Interacting with the Arrow Flight SQL Server via the New Python ADBC Flight SQL Driver Flight SQL JDBC can still be faster than a non-Arrow-based protocol/JDBC driver, because it avoids converting data on the server and takes advantage of Arrow Flight RPC for fast data transfer, optimizing 2 of 3 performance opportunities.īut, performance can be even better with ADBC. JDBC requires conversion to/from the native Arrow columnar format to a row-based format JDBC is familiar with. Note: while the data is transferred between the Flight SQL server and JDBC client is in Apache Arrow format, JDBC of course uses Java types. Many SQL IDE tools support loading 3rd party JDBC drivers so feel free to use your tool of choice.įor instructions on how to use DBeaver Community Edition with the Arrow Flight SQL JDBC driver - see this repo. Jdbc:arrow-flight-sql://localhost:31337?useEncryption = true&user =flight_username&password =testing123&disableCertificateVerification = true If you have Docker installed (and running) - you can run the server by opening a terminal and running the following command: By default, the container mounts a very small (scale factor 0.01) sample TPC-H database that you can query from a JDBC or ADBC client. To get started, you can run the secured Flight SQL server (all the code is stored here) by running our pre-built Docker container image. We will also query it with JDBC (for tool compatibility) and the brand-new, performance-optimized ADBC (Arrow Database Connectivity) drivers. In this post, we will show you how to run a Flight SQL server using a DuckDB backend. In our previous blog post, we discussed how Apache Arrow Flight SQL allows any compliant database to share data in the Apache Arrow columnar format while avoiding the speed penalty of serialization/deserialization bottlenecks. Running an Arrow Flight SQL Server and Querying Data with JDBC and ADBC Philip Moore, Tom Drabas, David Li
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