Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory
Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera.
Spark is an open-source solution, so there are no licensing costs.
Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera.
Spark is an open-source solution, so there are no licensing costs.
IBM Spectrum Computing uses intelligent workload and policy-driven resource management to optimize resources across the data center, on premises and in the cloud. Now up to 150X faster and scalable to over 160,000 cores, IBM provides you with the latest advances in software-defined infrastructure to help you unleash the power of your distributed mission-critical high performance computing (HPC), analytics and big data applications as well as a new generation open source frameworks such as Hadoop and Spark.
This solution is expensive.
Spectrum Computing is one of the most expensive products on the market.
This solution is expensive.
Spectrum Computing is one of the most expensive products on the market.
When comparing with Oracle Sybase and SQL, it's cheaper. It's not expensive.
The price could be better for the product.
When comparing with Oracle Sybase and SQL, it's cheaper. It's not expensive.
The price could be better for the product.