The primary goals for Firebird 3.0 were to unify the server architecture and to improve support for SMP and multiple-core hardware platforms. Parallel objectives were to improve threading of engine processes and the options for sharing page cache across thread and connection boundaries.
Alongside these aims came new strategies to improve performance, query optimization, monitoring and scalability and to address the demand for more security options. A number of popular features were introduced into the SQL language, including the long-awaited support for the Boolean data type and the associated logical predications.
Download it here.
A “Migration Guide to Firebird 3” eBook, written by Carlos H. Cantu, is also available.
The source code was just tagged in the repository, so we can expect the final release being out in the next days!
Are you prepared for Firebird 3? The Migration Guide to Firebird 3 eBook is here to help you to move quickly to Firebird 3. The eBook is available in English and in Brazilian Portuguese.
Firebird Project announces the second Release Candidate of Firebird 3.0, the next major version of the Firebird relational database, which is now available for testing.
Firebird Project is happy to announce general availability of Firebird 2.5.5 — the latest minor release in the Firebird 2.5 series.
This sub-release introduces several bug fixes and a few improvements, please refer to the Release Notes for the full list of changes. Binary kits for Windows, Linux and Mac OS X on both 32-bit and 64-bit platforms are immediately available for download.
Firebird Project announces the first Release Candidate of Firebird 3.0, the next major version of the Firebird relational database, which is now available for testing.
This Release Candidate demonstrates the complete set of features and improvements developed for the new release. Release Candidates are generally considered stable enough and may be recommended for testing in “almost-production” environments. Please report about any found bugs to the bugtracker.
Please read the Release Notes carefully before installing and testing this Release Candidate.
This version will make the build reproducible.
The reproducible builds initiative aims to enable anyone to reproduce bit by bit identical binary packages from a given source, thus enabling anyone to independently verify that a binary matches the source code from which it was said it was derived. For example, this allow the users of Debian to rebuild packages and obtain exactly identical packages to the ones provided by the Debian repositories.
Prune tool sets the creation stamp in the database header to a fixed value (taken from the last changelog stanza) and
prunes unused space on index/data pages of shipped databases
At the 12th Firebird Developers Day, I talked about Using Firebird in high latency networks (aka. internet). Below are two slides from my presentation, where you can see the improvements in Firebird 3 wire protocol, compared to FB 2.5 and to MySQL.
Obs: Left axis values are expressed in seconds. Test server was hosted in Amazon (USA) and client accessing it was located in Brazil. Ping reported latency of 219ms. The smaller the bar, the better.
Above graph shows the result of fetching 10.000 records from a real table used to store customers data. Red bars represents records with all the fields filled (ie: there was no fields containing nulls) and blue bars represents fetching records where some of the fields were nulls. Tests where done with and without compression.
The same table used in previous graph was created in MySQL InnoDB (same data). Blue bars means that wire compression was disabled, and red has compression enabled. Left side graphs has all fields filled (ie. there wasn’t null fields) and in right side graphs, some records has some null fields.
As you see, FB 3 won 😉
I should mention that there was no blob fields in the table, and this makes a lot of difference. Fetching non-null blobs makes the fetch slower in Firebird (more roundtrips are needed).
PS: The improvements in the FB 3 wire protocol were sponsored by donations collected in the 9th edition of FDD conference, and were implemented by Dmitry Yemanov. Compression was implemented by Alex Peshkov.