Feeds

Google forges BigTable-based NoSQL datastore

Takes out BigTable, thwacks Amazon DynamoDB over the head

SANS - Survey on application security programs

Google I/O If you're Google, building cloud services for the public must be frustrating – after spending a decade crafting and stitching together software systems for use internally, when you try and sell them to the outside world you need to unpick them from one another.

It seems more like butchery than creation, but that's the name of the cloud game, and so on Wednesday Google further fragmented its services by ripping a scalable NoSQL datastore away from Google App Engine (GAE) and making it into a standalone service named Google Cloud Datastore.

This strategy of designing integrated products and fragmenting them for the general public runs throughout Google's cloud history. For example, its cloud portfolio started out with platform services via GAE, but after Amazon started raking in vast amounts of cash from IaaS services on AWS, Google separated out basic VM services into the Google Compute Engine infrastructure cloud.

With Datastore, Google has taken another bit of App Engine and stuck it on its own plinth. The service is a columnar datastore which supports ACID transactions, has high availability via multi-data center replication, and offers SQL-like queries.

It will compete with Amazon's DynamoDB NoSQL row-based datastore. Though roughly equivalent in terms of capability, the two services have some architectural differences that influence how they work: BigTable-based Datastore has strong consistency for reads and eventual consistency for queries, whereas DynamoDB offers people a choice of eventual or strong consistency, depending on pricing. Both systems are heavily optimized for writes.

The systems' storage substrates also differ. DynamoDB uses an SSD-backed set of hardware, but Google indicated its Datastore may use both flash and disk. "We do use them [SSDs], we sort of use them behind the scenes," Greg DeMichillie, a Google Cloud product manager, told The Register. "Frankly we think what people really want is a certain performance level but they really couldn't care whether it's this technology or that behind it. We don't surface inside the storage stack where we happen to be using SSDs and where we don't."

The base cost for Google storage is $0.24 per gigabyte per month, with writes charged at $0.10 per 100,000 operations and reads charged at $0.07 per 100,000. This compares favorably with DynamoDB, which costs $0.25 per GB per month, plus $0.0065 per hour for every 10 units of write capacity, or $0.0065 per hour for every 50 units of read capacity. Harmonizing these two pricing approaches is difficult due to the labyrinthian price structure Amazon uses.

For both services, transferring data in costs no charge, but moving it to other storage or services can sting you, with Google charging $0.12 per gigabyte on outgoing bandwidth and Amazon charging on a sliding scale from $0.12 to $0.05 – or even lower, if you have a ton of data.

"With Datastore we certainly will continue to evolve over time onto latest and greatest versions," DeMichillie said. "It's really just a matter of timing and sequencing." ®

3 Big data security analytics techniques

More from The Register

next story
This time it's 'Personal': new Office 365 sub covers just two devices
Redmond also brings Office into Google's back yard
Kingston DataTraveler MicroDuo: Turn your phone into a 72GB beast
USB-usiness in the front, micro-USB party in the back
IBM rides nightmarish hardware landscape on OpenPOWER Consortium raft
Google mulls 'third-generation of warehouse-scale computing' on Big Blue's open chips
It's GOOD to get RAIN on your upgrade parade: Crucial M550 1TB SSD
Performance tweaks and power savings – what's not to like?
AMD's 'Seattle' 64-bit ARM server chips now sampling, set to launch in late 2014
But they won't appear in SeaMicro Fabric Compute Systems anytime soon
prev story

Whitepapers

Securing web applications made simple and scalable
In this whitepaper learn how automated security testing can provide a simple and scalable way to protect your web applications.
3 Big data security analytics techniques
Applying these Big Data security analytics techniques can help you make your business safer by detecting attacks early, before significant damage is done.
The benefits of software based PBX
Why you should break free from your proprietary PBX and how to leverage your existing server hardware.
Mainstay ROI - Does application security pay?
In this whitepaper learn how you and your enterprise might benefit from better software security.
Combat fraud and increase customer satisfaction
Based on their experience using HP ArcSight Enterprise Security Manager for IT security operations, Finansbank moved to HP ArcSight ESM for fraud management.