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Displaying posts with tag: Cloud Databases (reset)

Maria Update
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Image by Sebastian Bergmann via Flickr

I had a quick chat with Michael Widenius today.  He is on vacation so tried to keep the call short.  Essentially spoke about two topics, Oracle & an update on Maria.

The Monty Program has 15 staff now.  Their focus is getting the MariaDB branch of MySQL ready for release, I understand they have a target of next month (August) for this release.  The Maria storage engine has been delayed for the time being with the focus

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The NoSQL community needs to engage the DBA’s
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The NoSQL movement has been gaining some steam lately, with discussion forums and mailing lists popping up all around the web.  Despite having a career that has been centered on the RDBMS, I have made no secret that I think we have gone too far down with our RDBMS for everything mindset.  I think we need to add a few more tools back into our data toolbox. 

Today, 99.5% of new data centric developments started will use a RDBMS by default.  Maybe .5 of a % will consider using something as obtuse as a NoSQL platform.  By experience I know the majority of people discussing NoSQL platforms today are web developers.  In

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This post was a bit of a test to see if I could write a serious post about a database platform called Hamster.  I think I just made it :)

With all the noise over key/value stores recently, we should keep in mind that this technology isn’t exactly new.  It is being applied to new problems, but many of the foundations have been around for decades.  Probably the oldest of them all, Berkley DB came into existence during the mid ‘80’s and now has over 200 million deployments (according to the Oracle web site).

HamsterDB, while not having the same pedigree of Berkley, has been steadily worked on by

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HadoopDB discussion with Daniel Abadi
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I spoke to Daniel Abadi this morning about his HadoopDB announcement that came out a couple of days back.  I am sure this has been a busy time for Daniel and his team over in Yale as HadoopDB has been getting a lot of interest which I am sure will continue to build.

Some notes from our discussion:

  • HadoopDB is primarily focused on high scalability and the required availability at scale.  Daniel questions current MPP’s ability to truly scale past 100 nodes whereas Hadoop has real examples on 3000+ nodes.
  • HadoopDB like many MPP analytical database platforms

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Could MySQL be pigeon holed by Oracle love?
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Image by weboo via Flickr

A while ago, about 16 years ago now, I had a desktop computer.  It wasn’t a PC.  It was an Acorn.  It had an ARM processor in it.  Despite the rest of the world starting going crazy for the new Pentium chip, the Acorn with its ARM processor could run rings about it in terms of computing power.  And it was simple and easy to use, I used to write applications in assembly code for it (and it didn't have a fan!).

Not too long after that Acorn went under, Arm was already off on

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Forrester's EDM Wave
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Forrester put out its Enterprise Data Management Q2 2009 report a few days ago, you can buy it from Forrester but it also seems to now be available for free from Microsoft here.  I don’t actively seek out these reports as they usually just re-enforce common knowledge (this one was no exception), however as it turned up I managed to find some time on the weekend for a quick read through.

Few surprises in this report, but some key mentions are:

  • DBMS market expected to grow 8% annually
  • IBM, Microsoft & Oracle own 88% of the DBMS market (by revenue)
  • Current market estimated at $27 billion, $32 billion by 2013
  • IBM,
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Groovy Baby, Yeah
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(yeah, this company is going to have to get used to the Austin Powers references.)

Groovy Corp put out a press release last night that starts the official launch of their SQL Switch relational database platform.

I have been speaking with Groovy for a few months, and while the press release is a bit noisy there is actually some interesting stuff in it.

First, an overview

  • They are an in memory RDBMS
  • They have worked with Intel to architect from the ground up for large multi processor concurrency
  • Initially they are launching as a multi-core appliance
  • They claim

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The TPC Debate (yawn)
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Recently on a number of sites the benefits for and against have been debated with, on occasion, these conversations falling into abuse being thrown in both directions.

From a pure technical perspective, the TPC benchmarks make little sense and are probably not relevant to 99% of organizations looking to implement a database technology.  But as a tool for generating visibility, debate and improved public awareness of a vendors technology they still have an impact. 

This is marketing, pure and simple.  Having a great TPC result is akin to an author having a great review on Amazon.  Doesn’t mean it is relevant for you but if faced with a stack of titles you haven’t yet read you’ll probably look more closely at the ones you’ve heard

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Positioning your Database Start Up for Data Warehousing
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Image via Wikipedia

BI/Data Warehousing is an easier market to enter for new database platform vendors.  This is for a few reasons.  Firstly, most BI deployments are custom built projects for each organization.  This means the ability to pick and choose various layers of the stack is much greater. 

Secondly, BI/DW projects success/failure metrics are often tied to database platform driven properties – performance, scalability, load times etc.  The ability to stray outside any existing database platform “standards” to choose a platform that better meets key

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Positioning your Database Start Up for Enterprise OLTP
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Image by RaghuP via Flickr

It is important to realize that there is less diversity in the enterprise OLTP market than at any point in the last 20 years.  Essentially this market has been boiled down to Oracle, SQL Server & DB2 (with few isolated exceptions).   Most new deployments are typically using one of the first two options.  The lack of diversity has created a stalemate or chicken &

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How to Position your Database Start Up
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I have been speaking with a lot or new database vendors over the last 12 months and this has prompted me to revisit a post I wrote mid last year.  The basic premise of this post is that your strategy, and the group of people you’re selling to, largely depends on the market sector you are focusing on (Enterprise OLTP, BI/DW, Cloud & Web 2.0).

A database platform by itself is a largely pointless piece of software.  The only way value is produced from a database platform is through the applications that interact with it.  Therefore the only way to be a successful database platform is by making others successful and motivated to use your platform.

Ok, so as a database platform vendor how do you enter this market then? Well there are a few strategies.  Due to the length of this article I have broken it up into Enterprise OLTP, Enterprise Data Warehousing and Cloud & Web 2.0

Amusing Database Videos
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Oh my. This is just immensely funny & sad at the same time - Amusing Database Videos http://www.bigdatabaselist.com/wiki/Amusing_Database_Videos

Relational Databases Get a Hard Time
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Image via Wikipedia

The NoSQL event has triggered a bit of a hard time for the RDBMS the last week.  I won’t add any commentary as this follows what I have been talking about for a while, but here are some of the links.  Most notable is Michael Stonebraker’s post on the ACM site.

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The problem with the RDBMS (Part 3) – Let's Get Real
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Image by ToniVC via Flickr

  • Introduction
  • The Problem with the Relational Database (Part 1 ) –The Deployment Model
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    Graph Databases and the Future of Large-Scale Knowledge Management
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    Image via Wikipedia

    Todd Hoff has posted a link to a Los Alamos National Lab presentation on Graph Databases.  In this paper they provide a revisit on the classic RDBMS vs Graph database debate.

    The Relational Database hasn’t maintained its dominance out of dumb luck.  Instead the RDBMS has consistently outperformed while providing the most general use capability of all the variety of platforms that have been

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    The Argument For & Against Map/Reduce
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    The last 24 months has seen the introduction of Map/Reduce functionality into the data processing arena in various forms.  Map/Reduce is a framework for developing scalable data processing functionality, and was popularized by Google (see this earlier post).

    Pure players like Hadoop are starting to find their own niche, helped by organizations such as Cloudera.  However there has been a number of for & against arguments relating to Map/Reduce functionality inside the database.

    These arguments are now really serving a moot point.  Customers have recognized value in Map/Reduce prompting some (b)leading edge database vendors to

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    Top 10 interesting companies in Data Management
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    A bit of fun for a Sunday.  Below is the list of my top 10 interesting companies in Data Management right now.  Interesting to me means doing new stuff and being somewhat disruptive, or have a “watch and see” quality about them.  Note this is about companies not data management applications. 

    While I find a bunch of other data management applications interesting (PNUTS, Cassandra, Redis etc) these aren’t really encapsulated in a company with a go to market strategy.

    10gen - They are making interesting noises not sure about delivery yet
    Amazon – SimpleDB is neat, but not a grown up data platform yet
    Aster Data – Doing funky things with

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    Why you won't be building your killer app on a distributed hash table
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    A great post from Jonathan Ellis on "Why you won't be building your killer app on a distributed hash table"

    Scroll down to see my comment.  I agree a simple DHT is not a suitable solution for mainstream data management issues, but also I think that there is a gap between RDBMS and DHT.

    The Problem with the Relational Database (Part 2) – Predictability
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    I met with a friend of mine in New York recently who runs a credit card processing end-point company.  They specifically built their business around a non-relational database platform and feel they would have major issues had they chosen to build their business around a traditional

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    The Problem with the Relational Database (Part 1 ) –The Deployment Model
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    This is the first detail post in a series I am doing focusing on the issues that exist today with the Relational Database.  This first post is on the deployment model.  It could be argued that this isn’t directly related to the “relational database” but rather is an implementation model problem.  I disagree with this as many characteristics of the relational

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    The Problem with the Relational Database
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    The relational database has been the core mechanism for structured data storage and retrieval for the past 30 years.  My career so far has focused around the relational database, whether it be from a development, administrator or investment perspective.  In all this time the RDB has been the best generic option available for

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    Is the Relational Database Doomed?
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    Recently, a lot of new non-relational databases have cropped up both inside and outside the cloud. One key message this sends is, "if you want vast, on-demand scalability, you need a non-relational database".

    If that is true, then is this a sign that the once mighty relational database finally has a chink in its armor? Is this a sign that relational databases have had their day and will decline over time? In this post, we'll look at the current trend of moving away from relational databases in certain situations and what this means for the future of the relational database.[more]

    Top 10 Data Management Issues for 2009
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    So it’s that time of year again when everyone puts out their predictions for the year ahead.  I think predictions are a bit of a waste of time because to be interesting predictions have to be big, but a year really isn’t all that long so actual changes over the course of 2009 are likely to be just small progressions.  So instead I have been thinking about the top issues that we face heading into 2009 and here is my Top 10 list for issues in Data Management.  In this post I avoid offering solutions to these issues, while I have several ideas on solutions these can be the subject of subsequent posts.

    10 - Limits on Scalability

    While scalability is on my list it is at number 10 because against popular belief, scalability is only an issue for a very small number of data based applications.  Almost all data based

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    Previous 30 Newer Entries Showing entries 31 to 53

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