Oracle Database World 2021 In-Memory Sessions

 Oracle Database World 2021 In-Memory Sessions.

Oracle is hosting a new event called Oracle Database World 2021. Here is a summary of these very useful Oracle Database In-Memory sessions for Oracle Database World 2021:

•     Database In-Memory: Real Time Analytics, Supercharged, Andy Rivenes and Shasank Chavan
•     Superfast Event Stream Processing with a Converged Database, Tirthankar Lahiri and Shasank Chavan
•     Hands On Lab: Boost Analytics Performance with Oracle Database In-Memory, Andy Rivenes and Markus Kissling

Enjoy this blog post summarizing these very useful In-Memory Sessions at Oracle Database World 2021.

Cheers.

Oracle Database 21c New Features: In-Memory Vector Joins

 In-Memory Expressions in Oracle Database 21c: A Quick Primer.

This blog post by Andy Rivenes Product Manager at Oracle highlights this exciting new feature with Oracle Database In-Memory 21c.

Here is a quick summary:

• In-Memory Deep Vectorization is a new framework that has been added to Database In-Memory. 
• In-Memory Deep Vectorization is a SIMD-based (single instruction, multiple data) framework that supports vectorization for higher-level query operators in the query plan.
• In-Memory vectorized joins is the first feature that takes advantage of this new In-Memory deep vectorization framework. 
• This new feature speeds up in-memory joins and is transparent to the user.

Enjoy this blog post  highlighting this exciting new feature with Oracle Database In-Memory 21c.

Cheers.

You can now upgrade Grid Infrastructure to 19c on Gen2 Exadata Cloud@Customer

 You can now upgrade Grid Infrastructure to 19c on Gen2 Exadata Cloud@Customer.

This blog post by Prince Mathew Principal Product Manager at Oracle highlights this new announcement for Gen2 Exadata Cloud@Customer.

Here is a brief summary of this new upgrade to 19c capability on Gen2 Exadata Cloud@Customer.

• Run a precheck before upgrade to the 19c Grid Infrastructure version to identify and resolve compatibility issues in advance.
• Even if a precheck is not run, an implicit precheck will always be run as part of the GI upgrade workflow to ensure that the cluster is ready for an upgrade.
• Upgrade existing VM Clusters to 19c Grid Infrastructure version which is now a required step before upgrading databases on the cluster to 19c.
• The GI version upgrade to 19c is applied in a rolling manner across the cluster and does result in downtime for running database workloads. 

GI upgrade is a planned activity.

Enjoy this blog post announcing this much needed new upgrade capability for Gen2 Exadata Cloud@Customer.

Cheers.

Oracle Database In-Memory Youtube Channel and Summit Videos

Oracle Database In-Memory Youtube Channel and Summit Videos.

Session 1 & Session 2 Agenda:

• Oracle Database In-Memory: Warp Speed for the Enterprise!, Tirthankar Lahiri (40 minutes)
• Leverage Technology & Use In-Memory for Acceleration, Rich Niemiec (30 minutes)
• What’s new in Database In-Memory, Shasank Chavan (20 minutes)
• Best Practices for Getting Started, Andy Rivenes (20 minutes)

Session 3 Agenda:

• Utilizing Oracle In-Memory to improve Application Performance, Ahmed Alomari (30 minutes)
• Customer Presentations
  • Lufthansa - Oracle In-Memory Application for reduced latency in maintenance processes, Thorsten Pensky (40 minutes)
  • In-Memory Datawarehousing at STEF, Benoît Colas (40 minutes)

Session 4 Agenda:

• Utilizing Oracle In-Memory to improve Application Performance, Ahmed Alomari presentation (30 minutes)
• Customer Presentation
  • Hisense Database In-Memory case study (40 minutes), Dong Qu, Yu Xiao

Enjoy this blog post summarizing these very useful In-Memory Videos on their official Youtube Channel.

Cheers.

Oracle Database Consolidation with Oracle Autonomous Database by granular (GB) storage allocation and fractional OCPU

Oracle Database Consolidation with Oracle Autonomous Database by granular (GB) storage allocation and fractional OCPU.

  

This blog post by Ranganath Srirangapatna Ramachandra and Simon Law Principal Product Managers at Oracle summarizes the capabilities/features & usefulness of Oracle Database Consolidation with Oracle Autonomous Database by granular (GB) storage allocation and fractional OCPU.

Here is a quick recap.

• ​Oracle Autonomous Database is a self-managing database that gives users the added ability of end-to-end automation of tasks which are usually done by DBAs. 
• This feature applies to Autonomous Database on Autonomous Database on Cloud@Customer and Dedicated Infrastructure.
• You can now provision Autonomous databases using fractional OCPU and storage in GBs with Release Update 19.11 and higher.
• Fractional OCPU means you can create databases < than 1 OCPU using fractional units, from 0.1 to 0.9 OCPU, with up to 10 databases running on a single OCPU.
• Fractional OCPU and granular (GB) storage facilitates the Autonomous Database users to reduce costs through database consolidation.
• You can now achieve greated denisty utilizing the power of the Exadata Infrastructure without sacrificing the platform's performance, availability, and security. 
• Fractional OCPU databases will get performance-related resources allocated proportionally based on the number of OCPUs chosen with integer OCPU Autonomous databases/
• Enter a decimal OCPU count between 0.1 and 0.9 and specify the storage size in GB on the Create Autonomous Database page To create an Autonomous Transaction Processing database with fractional OCPU and storage allocation in GB. 
• Fractional OCPU is for < 1 OCPU. For OCPU >= 1, the increment must be in integer.

Enjoy this blog post summarizing the capabilities/features & usefulness of Oracle Database Consolidation with Oracle Autonomous Database by granular (GB) storage allocation and fractional OCPU.

Cheers.

First Database In-Memory Summit Announcement by Oracle

First Database In-Memory Summit Announcement by Oracle.

 First Database In-Memory Summit will be on June 8th and 9th: The registration is free at:  http://bit.ly/OracleDatabaseIn-MemorySummit

Keynote speakers:

Richard Niemiec - Chief Innovation Officer, Viscosity North America

Ahmed Alomari - Entrepreneur, author, and Oracle ACE

Other notable  speakers:

• Tirthankar Lahiri, Senior Vice President, Data and In-Memory Technologies
• Shasank Chavan, Vice President, In-Memory Technologies
• Andy Rivenes, Database In-Memory Product Management

Enjoy this blog post annoucing the very first First Database In-Memory Summit Announcement by Oracle.

Cheers.

The debate about Single Purpose Database VS Converged/Consolidated Databases: Which approach/architecture is better?

The debate about Single Purpose Database VS Converged/Consolidated Databases: Which approach/architecture is better?

Here is an excellent blog post by Maria Colgan Master Product Manager at Oracle Product Management summarizing the pros and cons of each approach. Here is a quick recap on this topic.

• Single-Purpose Databases / Purpose Built Databases
• Single-Purpose Databases or Purpose Built Databases are architected for a singular or small number of problems/workloads: they are rather simplistic in nature with lesser functionality.
• It is relatively easier to start development against Single-Purpose Databases because of their simplicity.
• Single-Purpose Databases mostly scale well because they do not offer strong consistency guarantees.
• Single-Purpose Databases end up costing significantly more in the medium to long run due to data fragmentation and higher maintenance costs.
• Single-Purpose Best-of-Breed Databases typically creates Vendor Lock-In.
• Single-Purpose Databases are generally used in boutique cases which, typically require higher performance requirements e.g. transaction processing systems.
• Converged/Consolidated Databases 
• Converged/Consolidated Databases cater to all types of data, workloads and development protocols.
• Eliminating data fragmentation also eliminates data contagion in Converged/Consolidated Databases enabling application logic/modules to use and reuse a shared data copy across the organization.
• Converged/Consolidated Databases enable more synergy for data and workloads making development faster.
• Converged/Consolidated Databases make it much simpler for developers to run stuff like Cloud, Autonomous/ML, extended SQL, spatial, blockchain, IoT etc. in one singular consolidated database rather than running them across distributed Single-Purpose databases.
• Converged/Consolidated Databases helps the overall ecosystem to be relatively lesser complex which results in lesser maintenance and development costs in the medium to long run.
• Summary
• The of Single-Purpose Databases or Purpose Built Databases should be well thought out for a very limited/focused set of problems/tasks as, they come at extra maintenance/cost in the medium to long run.

This video by Juan Loaiza & Andrew Sutherland gives a good summary on this debate.

I hope you got a quick overview of the pros and cons of this ongoing debate: Single Purpose Database VS Converged/Consolidated Databases: Which approach/architecture is better?

Cheers.