Worth Reading

For those who like to read database comparisions/benchmarks, here is one that probably all Firebird fans will like :)

During the registration process for the 12th edition of the Firebird Developers Day, people could donate money to the Firebird Foundation. In total, it was collected R$ 4.590,27 (~ USD 1.3k). The list of donors is available here.

Thanks to all who contributed! And remember that anyone can contribute, donating or becoming a member of the Firebird Foundation.

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The virtual session that Dmitry Yemanov gave last year in the 11th Firebird Developers Day is now publicly available in YouTube.

The audio is in English, and there are subtitles in PT-BR available. In this video, Dmitry talks about the most recent developments done in FB 3, comment about the reasons for the delays of the releases, what we can expect for the future, etc.

Obs: Please note that the session was recorded in August/2014.

Watch it now in YouTube.

shell@hwH30-U10:/data/local/tmp/firebird/bin $ ./isql employee
Database: employee
SQL> show version;
ISQL Version: LI-T3.0.0.31567 Firebird 3.0 Beta 2
Server version:
Firebird/Linux/ARM (access method), version “LI-T3.0.0.31567 Firebird
3.0 Beta 2”
on disk structure version 12.0


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Mr. Hartmann wrote on his blog

Last week, I posted a story about my interaction with a software developer who uses FireBird (FB) as a back-end for their software. The short version is that they left FB’s settings at default and were using a really, REALLY old version of FB. This caused the application to have massive (18 minute) load times and hang the entire server, with just one client connected. Bellow (in the article) are the changes I made to increase overall performance of the application and server.

In the 9th Firebird Developers Day, we collected donations to sponsor the enhancements of the Firebird wire protocol, to optimize the speed of communication in high latency networks (aka. internet). Dmitry Yemanov implemented the optimizations that were finally available for public testing with the release of the Firebird 3 Beta 1, a few days ago.

So, I decided to test the improvements. I set up a Windows remote server running FB 2.5 and 3.0 (beta1 and beta2), and used a database with a single “customers” table containing real life data (7,000 records and 61 fields). For the tests, I also created a second table with the same data, but in this one, the fields containing nulls were filled with random chars and numbers up to its size limit.

The test itself is very simple: retrieve all the fields from the first 5,000 rows from the tables, using isql (directing ther output to disk, since stdout is too “slow” and affects the results in a bad way), and check the time taken to do the fetchall. Each test was run at last twice (in sequence, filling the cache, etc), and the lowest value obtained was used for the comparison.

You can see the results below, and it is very promising! Thanks Dmitry and also Alex Peshkov (who implemented the zlib compression).

PS: There is one weird case where FB 3 was slower than FB 2.5. I already reported this do Dmitry, and he is investigating.

A full article (in portuguese) about the tests is available at FireBase. Thanks for Fernando Pimenta who “donated” the remote server for my use.

Protocol Graph

Update: Dmitry just sent me more information about the case where FB 2.5 got better performance than FB 3:

Actually, the problem is in the default batch size, not the new code itself. With all fields filled up to their max length, the protocol message size is quite similar between v2.5 and v3, the difference is less than 5%. But v3 always sends 8 packets at once while v2.5 may send 8 to 16 packets at once, depending on the message size. In your particular case, the batch size should be ~12-13 packets. This explains better performance of v2.5.

I need to find a way to adapt the new batching algorithm to better match the old one in such border cases.

Update 2 (21-jan-15): In a recent email exchange, Dmitry told me that he was able to fix the “problem” causing FB 2.5 to have better performance in that specific single case.

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