Blending MongoDB and RDBMS for ecommerce

Blending MongoDB with RDBMS for e-commerce

My name isSteve Francia @spf13

• 15+ years building e-commerce• Long time open source contributor• Entrepreneur• Hacker, father, husband, skate punk• VP Engineering @ OpenSky

My name isJustin Hileman @bobthecow

• 10+ years making the Internet awesomer• Open Source contributor• Vespa rider, swing dancer, coder, standardista• Software Engineer @ OpenSky

We work for OpenSky http://opensky.com

OpenSky is a new way to shopOpenSky connects you with innovators,trendsetters and tastemakers.You choosethe ones you like and each week they inviteyou to their private online sales.

OpenSky Loves Open Source• PHP 5.3• Apache2• Symfony2• Doctrine2• jQuery• Mule• HornetQ• MongoDB• nginx• varnish

We contribute to manyopen source projects and pioneer innovative solutions using them

OpenSky was the ﬁrste-commerce site built on MongoDB... also the ﬁrst e-commerce site built on Symfony2

Why NoSQL for e-commerce?Using the right solution for each situation

Data dilemma of e-commerce Pick One

Data dilemma of e-commerce Pick One• Stick to one vertical (Sane schema)

Data dilemma of e-commerce Pick One• Stick to one vertical (Sane schema)• Flexibility (Insane schema)

Sane schema

Sane schema• Works ... for a while

Sane schema• Works ... for a while• Fine for a few types of products

Sane schema• Works ... for a while• Fine for a few types of products• Not possible when more product types introduced

Let’s Use an Example

Let’s Use an Example How about we start with books

Book Product SchemaProduct {id:sku: General Productproduct dimensions:shipping weight: attributesMSRP:price:description:...author: Orson Scott Cardtitle: Enders Gamebinding: Hardcoverpublication date: July 15, 1994 Book Speciﬁcpublisher name: Tor Science Fiction attributesnumber of pages: 352ISBN: 0812550706language: English...

Seems simple enough

Seems simple enoughWhat happens when we add another vertical... say music albums

Album Product SchemaProduct {id:sku: General Productproduct dimensions: attributes stay theshipping weight:MSRP: sameprice:description:...artist: MxPxtitle: Panic Album Speciﬁcrelease date: June 7, 2005 attributes arelabel: Side One Dummytrack listing: [ The Darkest ... differentlanguage: Englishformat: CD...

Okay, it’s getting hairy butis still manageable, right?

Okay, it’s getting hairy butis still manageable, right? Now the business want to sell jeans

Jeans Product SchemaProduct {id: General Productsku:product dimensions: attributes stay theshipping weight: sameMSRP:price:description:...brand: Luckygender: Mens Jeans speciﬁcmake: Vintage attributes are totallystyle: Straight Cut different ... and notlength: 34width: 34 consistent acrosscolor: Hipster brands & makematerial: Cotten Blend...

Now we’re screwed

We need a ﬂexibleschema in RDBMS

We need a ﬂexibleschema in RDBMS We got this ... right?

Many approachesdealing with unknownunknowns in RDBMS

Many approachesdealing with unknownunknowns in RDBMS None work well

EAV as popularized by Magento“For purposes of ﬂexibility, the Magneto database heavily utilizesan Entity-Attribute-Value (EAV) data model.As is often the case, the cost of ﬂexibility is complexity -Magento is no exception.The process of manipulating data in Magento is often more“involved” than that typically experienced using traditionalrelational tables.” - Varien

EAV• Crazy SQL queries• Hundreds of joins in a query... or• Hundreds of queries joined in the application• No database enforced integrity

Did I say crazy SQL(this is a single query)

Did I say crazy SQL(this is a single query)You may have trouble reading this in the back

Selecting a single product

Single Table Inheritance (insanely wide tables)• No data integrity enforcement• Only can use FK for common elements• Very wasteful (but disk is cheap!)• Can’t effectively index

Generic Columns• No data integrity enforcement• No data type enforcement• Only can use FK for common elements• Wasteful (but disk is cheap!)• Can’t index

Serialized in Blob• Not searchable• No integrity• All the disadvantages of a document store, but none of the advantages• Never should be used• One exception is Oracle XML which operates similar to a document store

Concrete Table Inheritance (a table for each product attribute set)• Allows for data integrity• Querying across attribute sets quite hard to do (lots of joins, OR statements and full table scanning)• New table needs to be created for each new attribute set

Class table inheritance (single product table, each attribute set in own table)• Likely best solution within the constraint of SQL• Supports data type enforcement• No data integrity enforcement• Easy querying across categories (for browse pages) since common data in single table• Every set needs a new table• Requires a ton of forsight, as changes are very complicated

MongoDB to the Rescue

MongoDB to the Rescue• Flexible (and sane) Schema

MongoDB to the Rescue• Flexible (and sane) Schema• Easily searchable

MongoDB to the Rescue• Flexible (and sane) Schema• Easily searchable• Easily accessible

MongoDB to the Rescue• Flexible (and sane) Schema• Easily searchable• Easily accessible• Fast

Flexible schema

{ { sku: "00e8da9c", sku: "00e8da9d", type: "Audio Album", type: "Film", title: "Hoss", title: "The Matrix", description: "by Lagwagon", description: "Set in the 22nd century, Th asin: "B0000007QG", asin: "B000P0J0AQ", shipping: { shipping: { weight: 6, weight: 6, dimensions: { dimensions: { width: 10, width: 10, height: 10, height: 10, depth: 1 depth: 1 }, }, }, }, pricing: { pricing: { list: 1000, list: 1200, retail: 800, retail: 1100, savings: 200, savings: 100, pct_savings: 20 pct_savings: 8.5 }, }, details: { details: { title: "Hoss", title: "The Matrix",

pct_savings: 20 pct_savings: 8.5}, },details: { details: { title: "Hoss", title: "The Matrix", artist: "Lagwagon", director: [ "Andy Wachowski", "Larry Wa genre: [ "Punk", "Hardcore", "Indie Rock" ], [ "Andy Wachowski", "Larry Wach writer: label: "Fat Wreck Chords", actor: [ "Keanu Reeves" , "Lawrence Fis number_of_discs: 1, genre: [ "Science Fiction", "Action" ], issue_date: "November 21, 1995", number_of_discs: 1, format: "CD", issue_date: "May 15 2007", alternate_formats: [ Vinyl, MP3 ],original_release_date: "1999", tracks: [ disc_format: "DVD", "Kids Dont Like To Share", rating: "R", "Violins", alternate_formats: [ VHS, Bluray ], "Name Dropping", run_time: "136", "Bombs Away", studio: "Warner Bros", "Move The Car", language: "English", "Sleep", format: [ "AC-3", "Closed-captioned", " "Sick", aspect_ratio: "1.66:1" "Rifle", }, "Weak", } "Black Eye", "Bro Dependent", "Razor Burn", "Shaving Your Head", "Ride The Snake", ],

Queries

db.products.find( { name: "The Matrix" } );

db.products.find( { name: "The Matrix" } ); { "_id": ObjectId("4d8ad78b46b731a22943d3d3"), "sku": "00e8da9d", "type": "Film", "name": "The Matrix", "description": "Set in the 22nd century, The Matrix...", "asin": "B000P0J0AQ", "shipping": { "weight": 6, "dimensions": { "width": 10, "height": 10, "depth": 1 } }, "pricing": {

db.products.find( { details.actor: "Groucho Marx" } );

db.products.find( { details.actor: "Groucho Marx" } ); }, "pricing": { "list": 1000, "retail": 800, "savings": 200, "pct_savings": 20 }, "details": { "title": "A Night at the Opera", "director": "Sam Wood", "actor": ["Groucho Marx", "Chico Marx", "Harpo Marx"], "genre": "Comedy", "number_of_discs": 1, "issue_date": "May 4 2004", "original_release_date": "1935", "disc_format": "DVD",

db.products.find( { details.genre: "Jazz", details.format: "CD"} );

db.products.find( { details.genre: "Jazz", details.format: "CD"} ); "list": 1200, "retail": 1100, "savings": 100, "pct_savings": 8 }, "details": { "title": "A Love Supreme [Original Recording Reissued]", "artist": "John Coltrane", "genre": ["Jazz", "General"], "format": "CD", "label": "Impulse Records", "number_of_discs": 1, "issue_date": "December 9, 1964", "alternate_formats": ["Vinyl", "MP3"], "tracks": [ "A Love Supreme Part I: Acknowledgement",

db.products.find( { details.actor: { $all: [James Stewart, Donna Reed] }} );

db.products.find( { details.actor: { $all: [James Stewart, Donna Reed] }} ); }, "details": { "title": "Its a Wonderful Life", "director": "Frank Capra", "actor": ["James Stewart", "Donna Reed", "Lionel Barrymore"], "writer": [ "Frank Capra", "Albert Hackett", "Frances Goodrich", "Jo Swerling", "Michael Wilson" ], "genre": "Drama", "number_of_discs": 1, "issue_date": "Oct 31 2006", "original_release_date": "1947",

Wanna Play?• grab products.js from http://github.com/spf13/mongoProducts• mongo --shell products.js• > use mongoProducts

Embedded documents are great for orders• Ordered items need to be ﬁxed at the time of purchase• Embed them right in the orderdb.order.find( { items.sku: 00e8da9f } );db.order.find( { items.details.actor: James Stewart} ).count();

Why not NoSQL?Using the right solution for each situation

Data (like people) arereally sensitive when it comes to money

Stricter datarequirements for $$

Stricter data requirements for $$• For ﬁnancial systems any data inconsistency is unacceptable

Stricter data requirements for $$• For ﬁnancial systems any data inconsistency is unacceptable• Perhaps you’ve heard of ACID?

What about ACID?

What about ACID?Q: Is MongoDB ACID?

What about ACID?Q: Is MongoDB ACID?A: Kinda

Atomicity

Atomicity• MongoDB does atomic writes

Atomicity• MongoDB does atomic writes ... for single document changesets

Atomicity• MongoDB does atomic writes ... for single document changesets• $set, $unset, $inc, $push, $pushAll, $pull, $pullAll, $bit

Consistency

Consistency• MongoDB can enforce unique keys

Consistency• MongoDB can enforce unique keys ... but only on keys shared by every document in the collection

Consistency• MongoDB can enforce unique keys ... but only on keys shared by every document in the collection• MongoDB cant enforce referential integrity

Isolation

Isolation• // Pseudo-isolated updates db.foo.update( { x : 1 } , { $inc : { y : 1 } } , false , true );

Isolation• // Pseudo-isolated updates db.foo.update( { x : 1 } , { $inc : { y : 1 } } , false , true );• // Isolated updates db.foo.update( { x : 1 , $atomic : 1 } , { $inc : { y : 1 } } , false , true );

Isolation• // Pseudo-isolated updates db.foo.update( { x : 1 } , { $inc : { y : 1 } } , false , true );• // Isolated updates db.foo.update( { x : 1 , $atomic : 1 } , { $inc : { y : 1 } } , false , true );• But there are caveats...

Isolation• // Pseudo-isolated updates db.foo.update( { x : 1 } , { $inc : { y : 1 } } , false , true );• // Isolated updates db.foo.update( { x : 1 , $atomic : 1 } , { $inc : { y : 1 } } , false , true );• But there are caveats... • Despite the $atomic keyword, this is not an atomic update, since atomicity implies “all or nothing”

Isolation• // Pseudo-isolated updates db.foo.update( { x : 1 } , { $inc : { y : 1 } } , false , true );• // Isolated updates db.foo.update( { x : 1 , $atomic : 1 } , { $inc : { y : 1 } } , false , true );• But there are caveats... • Despite the $atomic keyword, this is not an atomic update, since atomicity implies “all or nothing” • An isolated update can only act on a single collection. Multi- collection updates are not transactional, thus not isolatable.

Durability

Durability• Mongo has this one covered

What doesMongoDB Support?

• Atomic single document writes • If you need atomic writes across multi-document transactions dont use Mongo • Many e-commerce transactions could be accomplished within a single document write

• Atomic single document writes • If you need atomic writes across multi-document transactions dont use Mongo • Many e-commerce transactions could be accomplished within a single document write• Unique indexes • This only works on keys used by the entire collection

• Atomic single document writes • If you need atomic writes across multi-document transactions dont use Mongo • Many e-commerce transactions could be accomplished within a single document write• Unique indexes • This only works on keys used by the entire collection• Isolated (not atomic) single collection updates. • Mongo does not support locking • There are ways to work around this

• Atomic single document writes • If you need atomic writes across multi-document transactions dont use Mongo • Many e-commerce transactions could be accomplished within a single document write• Unique indexes • This only works on keys used by the entire collection• Isolated (not atomic) single collection updates. • Mongo does not support locking • There are ways to work around this• It’s durable

There are ways toguarantee ACID properties in inconsistent databases

There are ways toguarantee ACID properties in inconsistent databases (or, as we call them, consistency impaired databases)

Optimistic concurrency

Optimistic concurrency• Read the current state of a product

Optimistic concurrency• Read the current state of a product• Make your changes with the assertion that your product has the same state as it did when you last read it

Optimistic concurrency in MongoDB

Optimistic concurrency in MongoDBWe’ll use an update-if-current strategy.

Optimistic concurrency in MongoDBWe’ll use an update-if-current strategy.This example is straight from the documentation:

Optimistic concurrency in MongoDB We’ll use an update-if-current strategy. This example is straight from the documentation:> t = db.inventory> p = t.findOne({sku:abc})> t.update({_id:p._id, qty:p.qty}, {$inc: {qty: -1}});> db.$cmd.findOne({getlasterror:1});{"err" : , "updatedExisting" : true , "n" : 1 , "ok" : 1}// it worked

Optimistic concurrency in MongoDB We’ll use an update-if-current strategy. This example is straight from the documentation:> t = db.inventory> p = t.findOne({sku:abc})> t.update({_id:p._id, qty:p.qty}, {$inc: {qty: -1}});> db.$cmd.findOne({getlasterror:1});{"err" : , "updatedExisting" : true , "n" : 1 , "ok" : 1}// it worked ... If that didnt work, try again until it does.

Optimistic concurrency• Read the current state of a product.• Make your changes with the assertion that your product has the same state as it did when you last read it.

Optimistic concurrency• Read the current state of a product.• Make your changes with the assertion that your product has the same state as it did when you last read it.• Its possible to use OCC to bootstrap pessimistic concurrency and fake row level locking

Optimistic concurrency• Read the current state of a product.• Make your changes with the assertion that your product has the same state as it did when you last read it.• Its possible to use OCC to bootstrap pessimistic concurrency and fake row level locking ... ask me about this some time

Optimistic concurrency control assumes anenvironment with low data contention

OCC works great forcompanies like Amazon• Amazon has a long-tail catalog• A long tail catalog lends itself well to optimistic concurrency, because it has low data contention

OCC fails miserably for

OCC fails miserably for• eBay

OCC fails miserably for• eBay• Gilt

OCC fails miserably for• eBay• Gilt• Groupon

OCC fails miserably for• eBay• Gilt• Groupon• OpenSky

OCC fails miserably for• eBay• Gilt• Groupon• OpenSky• Living Social

OCC fails miserably for• eBay• Gilt• Groupon• OpenSky• Living Social• InsertFlashSaleSiteOfTheMinute

Flash sales and auctionsare deﬁned by high data contention

Flash sales and auctionsare deﬁned by high data contention• The model doesnt work otherwise

Flash sales and auctionsare deﬁned by high data contention• The model doesnt work otherwise• They cant afford to be optimistic

Can we use pessimistic concurrency with a distributed NoSQL database?

BlendingNoSQL & RDBMSUsing the right solution for each situation

Our goal is to put as much in Mongo as possible• What makes more sense in RDBMS? • Inventory • Orders

Inventory requires• Row level locking (or table level locking)

Orders require• Row level locking (or table level locking)• Atomic writes (inventory decremented)• Transactions (3rd party processing)

Inventory & checkout transactions

Commerce is ACID In Real Life

1. I go to Barneys and see a pair of shoes I just have to buy.

1. I go to Barneys and see a pair of shoes I just have to buy.2. I call “dibs” (by grabbing them off the shelf).

1. I go to Barneys and see a pair of shoes I just have to buy.2. I call “dibs” (by grabbing them off the shelf).3. I take them up to the cash register and purchase them:

1. I go to Barneys and see a pair of shoes I just have to buy.2. I call “dibs” (by grabbing them off the shelf).3. I take them up to the cash register and purchase them: • Store inventory has been manually decremented.

1. I go to Barneys and see a pair of shoes I just have to buy.2. I call “dibs” (by grabbing them off the shelf).3. I take them up to the cash register and purchase them: • Store inventory has been manually decremented. • I pay for them with my trusty AmEx.

1. I go to Barneys and see a pair of shoes I just have to buy.2. I call “dibs” (by grabbing them off the shelf).3. I take them up to the cash register and purchase them: • Store inventory has been manually decremented. • I pay for them with my trusty AmEx.4. If all goes according to plan, I walk out of the store.

1. I go to Barneys and see a pair of shoes I just have to buy.2. I call “dibs” (by grabbing them off the shelf).3. I take them up to the cash register and purchase them: • Store inventory has been manually decremented. • I pay for them with my trusty AmEx.4. If all goes according to plan, I walk out of the store.5. If my card was declined, the shoes are “rolled back”

1. I go to Barneys and see a pair of shoes I just have to buy.2. I call “dibs” (by grabbing them off the shelf).3. I take them up to the cash register and purchase them: • Store inventory has been manually decremented. • I pay for them with my trusty AmEx.4. If all goes according to plan, I walk out of the store.5. If my card was declined, the shoes are “rolled back” ... out onto the shelves and sold to the next customer who wants them.

We follow the samemodel for e-commerce

1. Select a product.

1. Select a product.2. Lock the row or table and conﬁrm inventory.

1. Select a product.2. Lock the row or table and conﬁrm inventory.3. Purchase the product:

1. Select a product.2. Lock the row or table and conﬁrm inventory.3. Purchase the product: • Decrement product inventory

1. Select a product.2. Lock the row or table and conﬁrm inventory.3. Purchase the product: • Decrement product inventory • Process payment

1. Select a product.2. Lock the row or table and conﬁrm inventory.3. Purchase the product: • Decrement product inventory • Process payment4. Commit the transaction.

1. Select a product.2. Lock the row or table and conﬁrm inventory.3. Purchase the product: • Decrement product inventory • Process payment4. Commit the transaction.5. Roll back if anything went wrong.

Doctrine (ORM/ODM) to the rescue

Doctrine (ORM/ODM) to the rescue It would be possible without them, but were not that masochistic

Data we store in SQL• Order• Order/Shipment• Order/Transaction• Inventory

Data we store in MongoDB

Data we store in MongoDB• User • Event• Product • TaxRate• Product/Sellable • ... and then I got tired of typing them in• Address • Just imagine this list has• Cart 40 more classes• CreditCard • ...

We have themost boring SQL schema ever

CREATE TABLE `product_inventory` ( `product_id` char(32) NOT NULL, ìnventory` int(11) NOT NULL DEFAULT 0, PRIMARY KEY (`product_id`));CREATE TABLE `sellable_inventory` ( `sellable_id` char(32) NOT NULL, ìnventory` int(11) NOT NULL DEFAULT 0, PRIMARY KEY (`sellable_id`));CREATE TABLE òrders` ( ìd` int(11) NOT NULL AUTO_INCREMENT, ùserId` char(32) NOT NULL, `shippingName` varchar(255) DEFAULT NULL, `shippingAddress1` varchar(255) DEFAULT NULL, `shippingAddress2` varchar(255) DEFAULT NULL, `shippingCity` varchar(255) DEFAULT NULL, `shippingState` varchar(2) DEFAULT NULL, `shippingZip` varchar(255) DEFAULT NULL, `billingName` varchar(255) DEFAULT NULL, `billingAddress1` varchar(255) DEFAULT NULL, `billingAddress2` varchar(255) DEFAULT NULL, `billingCity` varchar(255) DEFAULT NULL,

Wait. How does inventory live in SQL?Isn’t that a property in one of your Mongo collections?

I thought you’d never ask!

CREATE TABLE `product_inventory` ( `product_id` char(32) NOT NULL, ìnventory` int(11) NOT NULL DEFAULT 0, PRIMARY KEY (`product_id`));CREATE TABLE `sellable_inventory` ( `sellable_id` char(32) NOT NULL, ìnventory` int(11) NOT NULL DEFAULT 0, PRIMARY KEY (`sellable_id`));CREATE TABLE òrders` ( ìd` int(11) NOT NULL AUTO_INCREMENT, ùserId` char(32) NOT NULL, `shippingName` varchar(255) DEFAULT NULL, `shippingAddress1` varchar(255) DEFAULT NULL, `shippingAddress2` varchar(255) DEFAULT NULL, `shippingCity` varchar(255) DEFAULT NULL, `shippingState` varchar(2) DEFAULT NULL, `shippingZip` varchar(255) DEFAULT NULL, `billingName` varchar(255) DEFAULT NULL, `billingAddress1` varchar(255) DEFAULT NULL, `billingAddress2` varchar(255) DEFAULT NULL, `billingCity` varchar(255) DEFAULT NULL,

Inventory is transient• Product::$inventory is effectively a transient property• Note how I said “effectively”? ... we cheat and persist our transient property to MongoDB as well• We can do this because we never really trust the value stored in Mongo

Accuracy is only important when there’s contention

Accuracy is only important when there’s contention• For display, sorting and alerts, we can use the value stashed in MongoDB • It’s faster • It’s accurate enough

Accuracy is only important when there’s contention• For display, sorting and alerts, we can use the value stashed in MongoDB • It’s faster • It’s accurate enough• For ﬁnancial transactions, we want the security and comfort of our RDBMS.

We keep inventory in sync with listeners

We keep inventory in sync with listeners• Every time a new product is created, its inventory is inserted in SQL

We keep inventory in sync with listeners• Every time a new product is created, its inventory is inserted in SQL• Every time an order is placed, inventory is veriﬁed and decremented

We keep inventory in sync with listeners• Every time a new product is created, its inventory is inserted in SQL• Every time an order is placed, inventory is veriﬁed and decremented• Whenever the SQL inventory changes, it is saved to MongoDB as well

Be careful what you lock

Be careful what you lock1. Acquire inventory row lock and begin transaction2. Check current product inventory3. Decrement product inventory4. Write the Order to SQL5. Update affected MongoDB documents6. Commit the transaction7. Release product inventory lock

Making MongoDBand RDBMS relations play nice

Products aredocuments stored in MongoDB

/** @mongodb:Document(collection="products") */class Product{ /** @mongodb:Id */ private $id; /** @mongodb:String */ private $title; public function getId() { return $this->id; } public function getTitle() { return $this->title; } public function setTitle($title) { $this->title = $title; }}

Orders are entitiesstored in an RDBMS

/** * @orm:Entity * @orm:Table(name="orders") * @orm:HasLifecycleCallbacks */class Order{ /** * @orm:Id @orm:Column(type="integer") * @orm:GeneratedValue(strategy="AUTO") */ private $id; /** * @orm:Column(type="string") */ private $productId; /** * @var DocumentsProduct */ private $product; // ...}

So how does an RDBMS have areference to something outside the database?

Setting the Productclass Order { // ... public function setProduct(Product $product) { $this->productId = $product->getId(); $this->product = $product; }}

• $productId is mapped and persisted• $product which stores the Product instance is not a persistent entity property

Retrieving ourproduct later

OrderPostLoadListeneruse DoctrineORMEventLifecycleEventArgs;class OrderPostLoadListener{ public function postLoad(LifecycleEventArgs $eventArgs) { // get the order entity $order = $eventArgs->getEntity(); // get odm reference to order.product_id $productId = $order->getProductId(); $product = $this->dm->getReference(MyBundle:DocumentProduct, $productId); // set the product on the order $em = $eventArgs->getEntityManager(); $productReflProp = $em->getClassMetadata(MyBundle:EntityOrder) ->reflClass->getProperty(product); $productReflProp->setAccessible(true); $productReflProp->setValue($order, $product); }}

All Together Now// Create a new product and order$product = new Product();$product->setTitle(Test Product);$dm->persist($product);$dm->flush();$order = new Order();$order->setProduct($product);$em->persist($order);$em->flush();// Find the order later$order = $em->find(Order, $order->getId());// Instance of an uninitialized product proxy$product = $order->getProduct();// Initializes proxy and queries the monogodb databaseecho "Order Title: " . $product->getTitle();print_r($order);

Read more about this techniqueJon Wage, one of OpenSky’s engineers, ﬁrstwrote about this technique on his personalblog: http://jwage.comYou can read the full article here:http://jwage.com/2010/08/25/blending-the-doctrine-orm-and-mongodb-odm/

Questions? http://spf13.com @spf13 http://justinhileman.com @bobthecow http://opensky.comPS: We’re hiring!! Contact us at jobs@opensky.com

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Blending MongoDB and RDBMS for ecommerce

by Steve Francia on Jun 09, 2011

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Blending MongoDB and RDBMS for ecommerce Presentation Transcript