{"id":4975,"date":"2014-10-21T09:00:01","date_gmt":"2014-10-21T17:00:01","guid":{"rendered":"http:\/\/formtek.com\/blog\/?p=4975"},"modified":"2014-10-23T20:29:44","modified_gmt":"2014-10-24T04:29:44","slug":"cloud-data-management-snowflake-a-relational-database-built-for-the-cloud","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/cloud-data-management-snowflake-a-relational-database-built-for-the-cloud\/","title":{"rendered":"Cloud Data Management: SnowFlake: A Relational Database Built for the Cloud"},"content":{"rendered":"

In a world where Big Data technologies like Hadoop, HPCC and SAP HANA dominate the attention among most of the data analytics crowd, it\u2019s almost an anomaly to hear anything about new relational database technology.\u00a0 But today is different.\u00a0 Today Snowflake Computing<\/a> is announcing the introduction of a new relational database that\u2019s totally optimized for the cloud.<\/p>\n

Relational dataset technology has been around for more than thirty years, and it\u2019s been more than a decade since the last architected-from-scratch relational database was built.\u00a0 Do we really need an alternative to SQL Server, Oracle DB, PostgreSQL, or MySQL?<\/p>\n

The founders of Snowflake thought relational databases needed a new design when then started the company in 2012.\u00a0 Their goal was to create a relational database that fully separates data from compute, to design a database engine that was built to easily comply with the fundamental principle of the cloud that scale up and down should be easy and fast, to be fully elastic.<\/p>\n

Existing cloud databases like SQL Azure have attempted to provide elastic scale-out capabilities with modest success.\u00a0\u00a0Scale out with SQL Azure<\/a>, for example, is possible using techniques like sharding, but successful scale out is only possible after architecting a data model that is amenable to sharding and modifying your data to fit that structure, a task that may not be very easy.<\/p>\n

The new SnowFlake database is at the heart of their cloud service offering: \u00a0a product that is targeting data warehousing and analytics, something that they’re calling the SnowFlake Elastic Data Warehouse. \u00a0The new SnowFlake database is fully SQL compliant and fully compatible with Oracle’s flavor of SQL. \u00a0It’s been benchmarked against a 128 node system running the TPC-DS benchmark and found to be fully compliant.<\/p>\n

While still in stealth mode, SnoweFlake approached 300 different potential customers, ranging from small startups to large established enterprises. \u00a0Currently 50 trials of the technology are under way, there are a number of paying customers, and there are five referenceable customers that include Adobe, Conde Nast, and Accordant Media. \u00a0SnowFlake has received venture capital from Sutter Hill Ventures, Redpoint Ventures and Wing Venture Capital.<\/p>\n

Bob Muglia<\/a>, former\u00a0president of Microsoft’s $16 billion Server and Tools Business and now\u00a0CEO at SnowFlake, commented that “we realized that you couldn’t really do any of these things with any of the existing solutions. We looked closely at what they could do with PostGreSQL, what\u00a0could we do with MySQL from a data warehouse side, and does Hadoop make any sense. And we came to the conclusion that all those systems, while they\u00a0had value to them, they were born in a different era before the cloud was created, and in order to build something new to take advantage of cloud\u00a0capabilities, we had to start from scratch.”<\/p>\n

Muglia continued, said that they asked “what if we made it really possible for people to leverage that cheap storage in the cloud,\u00a0but still had the flexibility to get the compute when they needed it? \u00a0That was really a fundamental insight that led us to creating an architecture that hadn’t been deployed in data warehousing and definitely not in the cloud.\u00a0And that is this notion that we can separate out storage, compute, and the metadata management. So in the cloud, we store our data in our internal format\u00a0on cheap scalable services, and in the Amazon case, on Amazon S3. To give people the ability to store that data in a very very cheap form so that they don’t have\u00a0to spend time worrying about whether they’re going to be able to afford to keep all of their data or to spend time figuring out what to throw away.”<\/p>\n

Three fundamental attributes of the SnowFlake Elastic Data Warehouse are:<\/p>\n