The point with NoSQL is flexibility and RDBMS is structure and guarantees.
About a year ago I started getting a strange feeling that
the noSQL community is busy re-creating RDBMS in minute detail.
Why did we bother in the first place?
On 4/27/2012 6:49 PM, Data Craftsman wrote:
> Some Polyglot Persistence(NoSQL) products started support server side
> scripting, similar to RDBMS store procedure.
> E.g. Redis Lua scripting.
> I wish it is Python when Cassandra has the server side scripting feature.
> "server side scripting support is an extremely powerful tool. Having
> processing close to data (i.e. data locality) is a well known
> advantage, ..., it can open the doors to completely new features."
> Charlie (@mujiang) 一个 木匠
> Data Architect Developer
> On Sun, Apr 22, 2012 at 9:35 AM, Brian O'Neill <firstname.lastname@example.org> wrote:
>> We are certainly interested. To get things moving we implemented an add-on
>> for Cassandra to demonstrate the viability (using AOP):
>> Right now the implementation executes triggers asynchronously, allowing you
>> to implement a java interface and plugin your own java class that will get
>> called for every insert.
>> Per the discussion on 1311, we intend to extend our proof of concept to be
>> we'll probably allow for ruby and groovy as well)
>> On Apr 22, 2012, at 12:23 PM, Praveen Baratam wrote:
>> I found that Triggers are coming in Cassandra 1.2
>> (https://issues.apache.org/jira/browse/CASSANDRA-1311) but no mention of any
>> StoreProc like pattern.
>> I know this has been discussed so many times but never met with
>> any initiative. Even Groovy was staged out of the trunk.
>> Cassandra is great for logging and as such will be infinitely more useful if
>> some logic can be pushed into the Cassandra cluster nearer to the location
>> of Data to generate a materialized view useful for applications.
>> Server Side Scripts/Routines in Distributed Databases could soon prove to be
>> the differentiating factor.
>> Let me reiterate things with a use case.
>> In our application we store time series data in wide rows with TTL set on
>> each point to prevent data from growing beyond acceptable limits. Still the
>> data size can be a limiting factor to move all of it from the cluster node
>> to the querying node and then to the application via thrift for processing
>> and presentation.
>> Ideally we should process the data on the residing node and pass only the
>> materialized view of the data upstream. This should be trivial if Cassandra
>> implements some sort of server side scripting and CQL semantics to call it.
>> Is anybody else interested in a similar feature? Is it being worked on? Are
>> there any alternative strategies to this problem?
>> Brian ONeill
>> Lead Architect, Health Market Science (http://healthmarketscience.com)
>> blog: http://weblogs.java.net/blog/boneill42/
>> blog: http://brianoneill.blogspot.com/