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Showing entries 1 to 7

Displaying posts with tag: VC (reset)

31 Essential Blogs for Startups & Scalability
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Read the original article at 31 Essential Blogs for Startups & Scalability

So many blogs, so little time! Here’s our list of the best we’ve found. Currently our favorite reader is Pulse pictured left. Starting to play around with flipboard too.

Nuts & Bolts Technical

Slashdot
One of the original tech blogs, that still covers lots of breaking news, and difficult topics. Very technical, with probing commentary. Beware the actual comments though, as they’re often full of immature

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Behind the Scenes at a Venture Capital Firm
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Last fall, before I joined Zendesk, I took a role as an Executive-in-Residence at Scale Venture Partners. A lot of people asked me about this, so I've written an article at GigaOm that describes my thought process and what I ended up working on.

While there are as many variations on the EIR position as there are venture firms, there are two flavors, generally speaking: Entrepreneur-in-Residence and Executive-in-Residence. Most firms have some experience with Entrepreneur-in-Residence programs.



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Is ScaleDB Using MapReduce? Competing with Hadoop?
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I’ve had a few VCs ask how we compare to Hadoop and companies using MapReduce. With Google blessing MapReduce, it seems to be the cool new thing. I figure I’m going to have to explain this to VCs, so I might as well blog about it.

MapReduce is a process of dividing a problem into small pieces and distributing (mapping) those pieces to a large number of computers. Then it collects the processed data and merges (reduces) it into a result set. Hadoop provides the plumbing, so users focus on writing the query and Hadoop handles the dirty work of mapping and reducing. Such a query, using a procedural language like Java, is more complex than a comparable SQL query, but more on that below.

So what is MapReduce good for? It really shines when you want to summarize, analyze or transform a very large data set. This is why it is well suited to web data. Map reduce

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Is ScaleDB Using MapReduce? Competing with Hadoop?
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I’ve had a few VCs ask how we compare to Hadoop and companies using MapReduce. With Google blessing MapReduce, it seems to be the cool new thing. I figure I’m going to have to explain this to VCs, so I might as well blog about it.

MapReduce is a process of dividing a problem into small pieces and distributing (mapping) those pieces to a large number of computers. Then it collects the processed data and merges (reduces) it into a result set. Hadoop provides the plumbing, so users focus on writing the query and Hadoop handles the dirty work of mapping and reducing. Such a query, using a procedural language like Java, is more complex than a comparable SQL query, but more on that below.

So what is MapReduce good for? It really shines when you want to summarize, analyze or transform a very large data set. This is why it is well suited to web data. Map reduce

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CAOS Theory Podcast 2008.12.05
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Topics for this podcast:

* Open source getting, and going without VC investment
* Oracle contributions to Linux and open source
* Sun’s latest moves with MySQL database and version 5.1
* Linux in high-end computing

iTunes or direct download (25:50, 6.0 MB)

Getting Rich Fast ?
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Lukas Kahwe Smith has an awesome post titled "Open Source is not making enough rich people richer" .
Indeed, there is much talk that the VC's , the Investors and different others aren't seeing the big money fast enough, according to them that is.
Does that mean that the open source industry is going bad ? Does that mean you can't make a living when working in the Open Source industry ?

Absolutely not, as he points out there are uncountable people gaining a good living with Open Source, developers working on the different projects as their day job, system administrators managing open source platforms. We are helping out customers to implement Open Source and Free Software. And there are numerous other Drupal, Mysql, Xen, shops out there. Some have their own open source products and create a



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Why $20 million for Kickfire?
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As Matt Asay recently mentioned in his post about Kickfire, the company just closed a Series B for $20 million. In today’s credit-scarce market where VC funding is flat/declining, $20 million is a lot of money, especially for a company whose product is still in beta. What’s more, there seems to be an investment bubble in the broader data warehousing space in which Kickfire participates (at last count, there were over two dozen vendors, the majority of which are relatively new entrants) and that bubble looks like it is starting to burst as witnessed by Microsoft’s recent acquisition of DATAllegro. So, are the Kickfire investors

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Showing entries 1 to 7

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