NoSQL Benchmarks NoSQL use cases NoSQL Videos NoSQL Hybrid Solutions NoSQL Presentations Big Data Hadoop MapReduce Pig Hive Flume Oozie Sqoop HDFS ZooKeeper Cascading Cascalog BigTable Cassandra HBase Hypertable Couchbase CouchDB MongoDB OrientDB RavenDB Jackrabbit Terrastore Amazon DynamoDB Redis Riak Project Voldemort Tokyo Cabinet Kyoto Cabinet memcached Amazon SimpleDB Datomic MemcacheDB M/DB GT.M Amazon Dynamo Dynomite Mnesia Yahoo! PNUTS/Sherpa Neo4j InfoGrid Sones GraphDB InfiniteGraph AllegroGraph MarkLogic Clustrix CouchDB Case Studies MongoDB Case Studies NoSQL at Adobe NoSQL at Facebook NoSQL at Twitter



Will Scalable Data Stores Make NoSQL a Non-Starter?

Once we’re no longer talking about serving data, but rather just about storing large volumes of it, NoSQL can seem nearly obsolete. For organizations willing to pay for data warehousing and analysis tools, the options are limitless: massively parallel software, data warehouse appliances, distributed file systems, and the list goes on. Pick your poison. Have lots of unstructured data to analyze and don’t want to pay for software? Try Hadoop. Plus, it might very well work with your existing data management software.

Now this is completely confusing… so I’ll not spend time trying to understand it.

But this other question sounds like a good one:

Will a scalable SQL option always win out against a NoSQL option? Even for unstructured data?

Just omit the reference to scalable and think about: 1) know-how and 2) tooling support. NoSQL databases do have a long way to go to become an equal option for everyone and every project (nb that’s not to say that NoSQL will actually fit all problems) .

Original title and link for this post: Will Scalable Data Stores Make NoSQL a Non-Starter? (published on the NoSQL blog: myNoSQL)