NoSQL market: All content tagged as NoSQL market in NoSQL databases and polyglot persistence
Two interesting charts from Stackdriver’s blog about database usage in AWS environments (nb: keep in mind these numbers are based only on Stackdriver’s users):
I wonder how the following charts would look:
- amount of data per database type
- avg. number of operations per database type
Original title and link: Relational vs NoSQL on AWS ( ©myNoSQL)
Holy cow! That’s a 4 followed by a 5… with no dots in between.
Derrick Harris for GigaOm: NoSQL startup DataStax raises $45M to ride Cassandra’s wave:
Cassandra’s success with such large users has to do with its ability to handle large-scale online applications that demand steady levels of performance, DataStax CEO Billy Bosworth told me. Scalability and performance have never been among Cassandra’s shortcomings, and the database is capable of replicating data across data centers. Large companies used to choose Oracle for applications that needed these capabilities, but now that NoSQL options are around and relatively mature, companies are rethinking whether the relational database model was ever really correct for some applications in the first place.
DataStax will use the funding to build out globally and invest in Apache Cassandra, the NoSQL open-source project and foundation for the company’s database distributions. The funding also signals a potential IPO for DataStax but much will depend on the direction of the markets, said CEO Billy Bosworth in an interview yesterday. “We are building the company for that direction (IPO),” he said. “A l lot depends on external factors. Internally, the company is already starting that process.”
According to my books:
- This is the largest round raised by a NoSQL company. It tops 10gen’s $45mil for MongoDB.
- This is the 3rd largest round raised in the new data market, after Cloudera’s $65mil. and Hortonworks’s $50mil. rounds.
Original title and link: $45millions more for DataStax ( ©myNoSQL)
A new IDC report by Carl Olofson and Dan Vesset puts the Hadoop market in 2016 at $812.8 millions. I don’t know how these numbers are calculated, but it feels like a low estimation. Maybe it’s the open source origin of Hadoop and the price of the Amazon Elastic MapReduce that will keep this market under the billion. Or maybe there are sectors of the market that could not have been included in the estimation.
The other numbers we currently have are from the BigData Market Analysis report by Wikibon which places the pure-players’ revenues at $311mil for 2012 (nb: the pure-player list also includes names that are not directly connected to Hadoop) and the NoSQL market report by Market Research Media placing the NoSQL market at $1.8bn by 20151. Last but not least, based on the Splunk IPO we already know there’s a lot of market interest.
Original title and link: Hadoop Market in 2016: $813mil ( ©myNoSQL)
Couple of things I don’t see mentioned in the RedMonk post:
if and how data has been normalized based on each connector availability
According to the post data has been collected between Jan.2011-Mar.2012 and I think that not all connectors have been available since the beginning of the period.
if and how marketing pushes for each connectors have been weighed in
Announcing the Hadoop connector at an event with 2000 attendees or the MongoDB connector at an event with 800 attendeed could definitely influence the results (nb: keep in mind that the largest number is less than 7000, thus 200-500 downloads triggered by such an event have a significant impact)
Redis and VoltDB are mostly OLTP only databases
Original title and link: NoSQL Databases Adoption in Numbers ( ©myNoSQL)
But some early adopters of Hadoop now say using the technology is challenging and rolling it out will take time.
Mr. Boroditsky says Hadoop is “immature” and comes with additional costs of hiring in-house expertise and consultants. “There is a very substantial cost to free software,” he says, declining to comment on dollar figures.
I’m starting to believe that the “Hadoop has problems and is complex” chorus is a vendor reaction very similar to the reaction they had to open source in general. Thus, before joining the group complaining about the complexity, costs, and lack of know-how, ask yourself the following questions:
how many other tools can lead you to the same solution?
Here are a couple of examples of what people choosing Hadoop had to say:
We started exploring the NoSQL solutions more than a year ago. We did some research on the available solutions and chose Hadoop/HBase for few reasons: 1. Java based 2. Open source 3. Hadoop - quite mature compared to other Java based solutions. Hadoop is also used by many web companies. 4. HBase - using Hadoop (so you get for free Hadoop stability, APIs etc.), like BigTable
We tested this solution for 6 months (as a small cluster) and were very happy with it.
The quest for a solution began in 2009 with an investigation of Zion’s existing Microsoft and Oracle technologies, as well as other technologies within the firm and new solutions on the market, Wood relates. After developing a list of six potential vendors, he says, he and his team quickly focused on two Hadoop-based solutions. The team, Wood explains, recognized the potential in Hadoop for “making security decisions proactively rather than reactively, based on mining business intelligence and combining it with event data from security devices.”
based on the list of tools helping you solve the same problem:
- how many are cheaper for your scenario?
- for how many of them you’ll find more resources?
- how many are operationally simpler?
how many of these tools evolve as fast as Hadoop and its ecosystem?
how many of them allow you to go beyond the initial scenario and start addressing other questions?
Here is what people say about what happens after adopting Hadoop.
It would be great if Hadoop administration would get simpler and operational costs would go down and if know-how would be easier to find. Rest assured that all these will happen. And if for the time being these are problems you cannot overcome, tell me about the alternatives.
Original title and link: Hadoop Has Promise but Also Problems… Show Me the Cheaper or Simpler Alternatives ( ©myNoSQL)