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The New Acquisition Playbook: IP and Talent Over Companies

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  The tech landscape is constantly evolving, and with it, the strategies for growth and innovation. Recent events, particularly the Windsurf acquisition and the Character.ai deal with Google, highlight a burgeoning trend: large corporations are increasingly opting to acquire intellectual property (IP) and founding teams rather than entire companies. This shift signals a more surgical approach to M&A, focusing on specific assets and expertise that can accelerate internal development and maintain agility. The Windsurf Saga: A Case Study in Strategic Asset Acquisition The Windsurf acquisition by Cognition is a prime example of this new playbook in action. Initially, OpenAI was reportedly in talks to acquire Windsurf, an AI coding startup, for a hefty $3 billion [9]. However, the deal ultimately fell through, and in a dramatic turn of events, Google swooped in to poach Windsurf's CEO and co-founders [8]. Following this, Cognition announced its acquisition of Windsurf, specificall...
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Why I think In Memory Data Management was made for cloud

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http://upload.wikimedia.org/wikipedia/commons/b/b5/Cloud_computing.svg







Recently, I came across a nice blog on why Amazon thinks big data was made for the cloud. It talks of how big data and cloud computing will work hand in hand to create a central platform for communities to share huge Data Set.  In Memory Data management such as HANA enables this symbiotic relationship between the cloud and big data by facilitating on the fly reorganization of data






  1. Separate Database for customers
  2. Shared Database, Separate Schemas for customers
  3. Shared Database, Shared Schema for customers

Of the three approaches, the shared schema approach has the lowest costs, because it serves largest number of tenants per database server. Also, the administrative and hardware/software costs are drastically reduced. But, it comes with one complexity: As the customer isolation is the minimal, stringent database management  is required to ensure that tenants can never access other tenants' data, even in the event of unexpected bugs or attacks. Dynamic reorganization of Data is one of the prime requirements.

In Memory Databases such as HANA leverages the positives of columnar databases so that
  • New Attributes can be added easily vis-à-vis a row based database architecture
  • Locking for changing the data layout in only required for a short period contrary to row based architecture where the entire database or table would be completely locked to process data definition operations

I feel that there is a  great applicability of In Memory Data Management in cloud. Do give in your comments/ feedback on this piece.

Comments

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