Summer has arrived and so too has a new DBeaver PRO release. Today, we are glad to share the main updates of the 24.1 version with you.
The first thing we want to talk about are big changes that have been made to the Dashboards feature in the new release. Dashboards help technical specialists to quickly identify performance, disk space issues, the number of connections, and other important KPIs in a chart format. Previously, DBeaver applications only had predefined charts for several database types and the ability to create custom ones with a limited set of parameters supported by a specific database driver.
The 24.1 version integrates custom web-based charts into your dashboards. It enables a flexible way to display data from any accessible URL. You can add as many different charts as you need, customize the dashboard presentation, and monitor how your data changes in real-time.
Additionally, if you log into your Tableau account using the DBeaver app, all the charts created in this service will be accessible in the Dashboards view. After establishing a connection to your Tableau database in DBeaver, you will be able to not only edit data, but also monitor all the applied changes in real-time in the Dashboards view.
We continue to expand the AI capabilities of all our products. This time, we have added support for Llama, a family of autoregressive large language models released by Meta AI last year. DBeaver allows you to use any LLama-based models, including ones created by different vendors.
With Llama, you can avoid one of the main issues of using artificial intelligence — the need to transfer information about the database structure to a third-party resource.
Now you can import any Llama-compatible AI models hosted on your server or even on your personal computer to DBeaver, and switch between them in the Engine Settings of the AI Assistant preferences.
The following updates are related to the Data Compare feature in our desktop applications, including the desktop version of DBeaver Team Edition. Firstly, we have improved the performance for the large tables comparison. If you need to use this feature for tables with thousands or even millions of rows, uncheck the box “Store results in memory” at the Compare settings step. In this case, the results will be stored in a specially created temporary database. Thanks to this, you will not only avoid running out of memory but you will also speed up the comparison process.
Secondly, we have added the option of exporting Data Compare results into an HTML report. It can be helpful if you want to quickly explore all the differences between your tables or share the comparison results with your colleagues.
The capability of loading data to a database is crucial for many of our users, which is why all our desktop apps have had this feature for a long time. For this release, we have implemented data import functionality to CloudBeaver and the web version of DBeaver Team Edition. From the latest version, you can load data from CSV, XML and XSLX files to your database tables.
Our team will expand this functionality in future releases. We would be glad to get your feedback to make further improvements. Data import also works in the CloudBeaver Community, but it only supports the CVS file format.
If you use our web solutions and want to prevent accidental changes to the database, try using the new commit mode. You can easily switch between auto commit and manual commit using the top toolbar of CloudBeaver and Team Edition.
The manual commit mode works for each table in your active connections and helps you control all edits made in both the Data Editor and the SQL Editor. To cancel all the changes, click the Rollback button.
And finally, a couple of words about database support. We are pleased to announce our new partnership with Salesforce Data Cloud and share that our team keeps improving the support for this data source. This time, we have updated the driver to the newest version and added the ability to authenticate via OAuth.
Many updates in the desktop editions of DBeaver are related to Neo4j, a high-performance graph database. Now you can view all your data in a common grid view and JSON presentation, and perform queries using the specific Cypher syntax.
In addition to the points listed above, we have provided support for the older versions of Oracle and have added the ability to create a connection to AlloyDB via Cloud Explorer. We have also added links to our Wiki pages in the main section of the Connection Wizard for a large number of databases to make it easier for our users to perform all the connection settings correctly.
Of course, it is impossible to give you a detailed description of all our latest updates in one blog post. Therefore, if you want to learn about all the changes, we invite you to read our release notes and download the new version.
