OpenText is announcing the release of
Product: Analytics Database 25.4
Version: 25.4
Languages: English
The following new key features are available with this version:
- External Archives for Disaster Recovery
- Ability to replicate the DB for disaster recovery without having a live cluster. Customers can manage full state backups in multiple data centers easier, including across clouds, buckets and regions. That brings more confidence in the product. The DR story is always an important part of any deal.
- Built-in auto tuning
- Improve better default settings for auto projections. We will introduce algorithms to periodically generate efficient projection plans and apply them. The outcome is that customers can avoid manual tuning in common scenarios.
- Online upgrades for non-K8s
- Extend current K8s online upgrade to other environment settings like on-prem. Reduce the need for additional resources during the online upgrade. Reduce hiccup time and improve performance. Outcome is that non-K8s customers can leverage online upgrades to reduce down time.
- Support writes to Iceberg
- Important basic functionality for our data-lake story. Write to Iceberg is on the checklist of many customers we talked to. The outcome is that customers can run to write query results into Iceberg managed external files via standard SQL.
- External query usage tracker
- Accurate key metrics tracking of usage on external data source at query level, such as bytes, rows, etc. Such metrics will be aggregated and persisted in the database. The outcome is that customers will have better visibility into their external table query executions, resulting in better cost control and performance optimization.
- Variable length data (Performance side)
- Fundamentally redesign string data representation in memory and data structure in the core server query execution engine so that string-typed data (including primitive strings, binaries, arrays/vectors, complex data types, JSON, etc.) with high variance in size can be processed more resource efficiently and performant. This also eliminates the need to specify bound for string-typed data, which significantly improves usability. This is also a prerequisite for Iceberg full support, where Iceberg metadata has no bounds for string typed data.
- Vector Ops Functions
- Provide most common built-in distance functions for Vector Ops and maintain performance at scale. Combined UDT projection as indexing to speed up the vector search even more. Provide and SDK for future extensibility. The outcome is that customers can directly apply vector search in Vertica as part of their AI tech stack, which can motivate them to increase their Vertica footprint making us more relevant in the AI trend.
- Variable length data (Upgrade side)
- Supporting packed VL Data means that our plan execution will be more performant and efficient for wide variable-length columns, which has been a sticking point in the past. Focus on Scan, Load, and ExprEval as the highest-impact operators.
- Compute node MVP
- Better cluster scalability. This new architecture will further extend the scaling limit to thousands of nodes and beyond. In addition, compute node is more resource efficient and easy/fast to add/remove, making rapid auto scaling a viable solution. The outcome is that we can market our solution with unlimited scale and cost efficiency, which will significantly increase the confidence of current customer base (proven with real examples) and interest in prospects.
- Automated Certificate rotation in K8s
- This enables easier management of certificates across product components such as database operation, client connection, inter-node data / control message channel, etc. This work also includes proper rollback mechanism for robust automation. The outcome will be enhanced security level (encrypting everything and periodically rotating certificates) while bringing management complexity behind the scenes.
- K8s monitoring and troubleshoot aid setup
- This work integrates default dashboard (Grafana & Loki) to K8s deployment, so that users can monitor their database and analyze logs without necessary manual setup. The outcome is better user experience and security standard - no need to grant access pods.
- CI/CD Migration
- Move Vertica server Jenkins build CI/CD to OpenText GitLab as per company guidelines.
- Health Watchdog integration into vCluster UI
- Integrate recently released "health watchdog" into vCluster UI, the new gen of management/admin console UI for all types of deployments. This work will improve the visibility and provide clear steps, explanations and suggestions. The outcome is better user adoption of health watchdog, which improves cluster stability for long term.
For more information, please check the Release Notes for this version (available from MySupport).
If you have an active support subscription for these products, please plan for downloading this version from the Software Licenses and Downloads Portal. To access these products in the Software Licenses and Downloads Portal, you will need to sign in with your Micro Focus credentials.
Our goal is to provide you with clear visibility into the support time-line of software products, enabling you to use this information to plan, test, and deploy new product versions. For more information, check our Product Support Lifecycle pages. Please take note of the end of support dates for the latest available version of this product:
|
Product version |
Current Maintenance ends |
|
Analytics Database 25.4 |
Oct 31, 2028 |
Please note that all Analytics Database customers with active support subscriptions are eligible to update to Analytics Database 25.4.
