Today’s database landscape isn’t just static. It’s positively retro. Remember 2004? Facebook had just launched, the iPad wasn’t even a twinkle in Steve Jobs’ eye, and Gartner’s database market share report put IBM (34.1%), Oracle (33.7%), and Microsoft (20%) in the top spots. In our survey, Microsoft, Oracle, and IBM still hold the top spots; we do add MySQL, but that’s about it for innovation. […]
And those relational databases from Microsoft, Oracle, and IBM? They’re essentially just updated versions of the companies’ 2004 offerings.
You’ll see these numbers in many surveys. But there are a couple of things to keep in mind while reading them:
- the enterprise world is well-known to be a late adopter. A very late adopter actually.
- many of these databases are subscription based so customers are locked-in on at least an yearly basis
- many of these databases have been acquired together with hardware and consultancy/support. Another type of lock-in.
- none of these databases is showing the growth in demand, jobs, and revenue that the top NoSQL databases are seeing for the last 12-18 months.
When you already bought a house, it’s quite difficult to go out looking for a new one. But there’s no good reason for you not to look and get the best appliances and furniture for your house.
Original title and link: 2014 State Of Database Tech: Think Retro ( ©myNoSQL)
myNoSQL’s supporter Aerospike is getting ready for a new case study webinar:
As the industry’s largest online data exchange, BlueKai knows a thing or two about pushing the limits of scale. Find out how they are processing up to 10 trillion transactions per month from Vice President of Data Delivery, Ted Wallace.
Original title and link: April 3 Webinar: The BlueKai Playbook for Scaling to 10 Trillion Transactions a Month [sponsor] ( ©myNoSQL)
Words from the special myNoSQL sponsor, Couchbase:
You can’t judge a book by its cover, but you can judge the architecture of a distributed system by its topology.
If two distributed systems are equally effective, is the one with the simpler topology the one with the better architecture? This article compares the architecture of two document databases and two wide column stores by looking at their topologies.
Wow. There is a lot going on here. There are four node types and two layers of logical groupings.
Nice. Simple. There is one node type.
Which document database would you choose?
- Which one is going to be easier to deploy?
- Which one is going to be easier to maintain?
- Which one is going to be easier to scale?
- Which one is going to be more resilient?
I believe the less moving parts, the better.
Original title and link: Topology: The Architecture of Distributed Systems [sponsor] ( ©myNoSQL)
Snapdeal selects Aerospike to improve shopper satisfaction over MongoDB, Couchbase and Redis [sponsor]
Words from the long time myNoSQL supporter, Aerospike, reporting on a success story of a customer deploying Aerospike to deal with massive demand growth:
After experiencing 500% growth in 2013, Snapdeal, India’s largest online marketplace, switched from 10 MongoDB servers to just two Linux servers on Amazon EC2 with Aerospike, and reduced response times to less than a millisecond.
Read the case study to learn more.
Original title and link: Snapdeal selects Aerospike to improve shopper satisfaction over MongoDB, Couchbase and Redis [sponsor] ( ©myNoSQL)
A 4-part series by Mike Bostock describing various integrations paths of D3 and CouchDB:
- Part 1: saving a D3 app in CouchDB
- Part 2: storing D3 library in CouchDB and storing data in CouchDB
- Part 3: accessing CouchDB data from D3
- Part 4: data import
Original title and link: Integrating D3 with CouchDB ( ©myNoSQL)
In the words of the special sponsor, Couchbase:
Kelly knew it. The U.S. Navy knows it. You know it.
Keep it Simple, Stupid (KISS)
We categorized NoSQL implementations. The categories include distributed caches, key / value stores, and document databases. However, what if application requirements span multiple categories? Do you add Redis, Riak, and MongoDB? The result would not be simple, stupid.
Let distributed caching, key / value storage, and document handling be use cases. The solution is a single NoSQL implementation that supports multiple use cases. In fact, Viber recently solved this problem. Their previous architecture relied on MongoDB for document processing and Redis for distributed caching. Their current architecture relies on Couchbase Server as a single replacement for both MongoDB and Redis. Read the full story.
Original title and link: The NoSQL KISS [sponsor] ( ©myNoSQL)