The HP Hadoop Platform provides high performance and scalability for big data workloads. It offers several components for high throughput processing with MapReduce and TEZ, as well as lower latency querying with Presto. The platform also includes Spark for in-memory computation and machine learning, OpenTSDB for time series data, and Solr for scalable search capabilities.

1. HP Hadoop Platform
High Performance – High Throughput and Low Latency

2. HP Hadoop Platform
Reliable Scalable Cost Effective

3. • Execute High through put Transformations
• High Reliability and fault tolerance
• MR Engine for High Throughput
• TEZ for faster response
• Hive - High Productivity for SQL Developers
• Pig – Flow visualization makes understanding easy
• Pig and Hive Integration using HCatalog
HP Hadoop Platform
Hive/Pig– High Throughput Queries

4. • Presto is in-memory based- stores query results in memory and subsequent
operations on query result are faster.
• Presto works on top of HDFS and YARN
• Leverages Hive Meta store
• Offers flexibility in deployment- Can be deployed on few nodes in cluster
• HDP Certified release available
HP Hadoop Platform
Presto – Low Latency Queries

5. • HDFS Storage– Data Locality. Suited for Lambda architecture
• On top of HBase/Big Table columnar storage
• Consistency in CAP theorem
• Linear Scalability
• HTTP API for pulling Readings.
• Write with millisecond precision
• Integrates with Visualization tools
OpenTSDB – Time Series Solution
HP Hadoop Platform

6. • In Memory computation engine
• 100x faster than MapReduce.
• Ships with ML Lib – Machine Learning Library
• Usable with Scala/Python/R/Java
• Integrates with Kafka, Hive SQL, OpenTSDb
• GraphX/Graph Frame – Graph Query Capabilities
HP Hadoop Platform
Spark – Speed up Computation and ML

7. • Supported on Hortonworks Platform
• Based on Lucene Search engine
• HDFS Storage – Scalable storage
• Solr Cloud - Distributed architecture
• Near Real-Time Indexing
• Phonetic Matching supported
HP Hadoop Platform
Solr Indexing – Scalable Search