Our team recently integrated Vertica with the existing DataStax Cassandra tech stack in non-prod region.
On Day-1 PreProd end-end processing, the performance results are really impressive with an average of 90% improvement. As an example, 20 mins Hive job is slashed down to 2 mins Vertica fetch.
Technology Trade Secrets are:
- In-memory execution rather than disk I/O processing
- Powerful In memory of 256 GB RAM with 12 Core on each node
- Proprietary high performance(MPP) appliances like terradata, exadata
- Column oriented (traditional row-oriented) database for speedy fetch/analytic
- In-memory distributed processing (inspired by MapReduce algorithm)
- High level of in-built compression & encoding in data abstraction
- High availability using replication factor on cluster nodes
Recently Facebook selected the HP Vertica Analytics Platform as one component of its big data infrastructure. Ref:http://www.vertica.com/2013/
12/12/welcoming-facebook-to- the-growing-family-of-hp- vertica-customers/
Choosing the right technology for right use case is key to success in Big Data platform. Njoy the Continuous Learning on Big Data next generation.