451 Research is a leading IT research and advisory company founded in 2000 with over 250 employees including over 100 analysts. It provides research and data through fifteen channels to over 1,000 clients on technology and service providers. The document discusses the evolution of the meaning of "Hadoop" from referring originally to specific Apache projects like HDFS and MapReduce to becoming a catch-all term for the distributed data processing ecosystem, and how different Hadoop distributions combine various related Apache projects in their offerings. It also examines how data platforms are converging, with various databases, analytics engines, and streaming platforms increasingly supporting common workloads and data models.
451 Research is a leading IT research and advisory company founded in 2000 with over 250 employees including over 100 analysts. It provides research and data through fifteen channels to over 1,000 clients on technology and service providers. The document discusses the evolution of the meaning of "Hadoop" from referring originally to specific Apache projects like HDFS and MapReduce to becoming a catch-all term for the distributed data processing ecosystem, and how different Hadoop distributions combine various related Apache projects in their offerings. It also examines how data platforms are converging, with various databases, analytics engines, and streaming platforms increasingly supporting common workloads and data models.
The document contains SQL statements and execution plans for counting records in a table where the ID is between 1 and 10 and the status is either '00' or '01'. It shows that for a status of '00' there are 10000 records, but for a status of '01' there are 0 records. Execution plans and statistics are provided with each statement to analyze the performance and resource usage.
The document contains log and monitoring data from an Oracle database. It includes statistics on CPU and disk usage, wait events, load averages, and a list of SQL statements with metrics like parse time, execute time, fetch time and row counts. Times are recorded from 23:48 to 23:49 and include usernames like SCOTT interacting with the database.
This document provides an overview of infrastructure automation tools like Chef, Puppet, Ansible, Serverspec, Infrataster and the Infrataster OracleDB plugin. It includes steps to setup the Oracle Instant Client, install necessary Ruby gems, write an Infrataster spec test to query the Oracle database and assert that the db_block_size parameter equals 8192, and execute the spec test with RSpec.
This document contains several database query results. The first result shows the database version and current user. Subsequent results show additional data from database tables, including column names and values like the database name, version number, and identifiers.
The document discusses SAP HANA, a platform for online transaction processing (OLTP) and online analytical processing (OLAP). It notes that SAP HANA allows for one copy of data to support both OLTP and OLAP workloads. It also discusses key capabilities of SAP HANA like advanced compression, multi-tenancy, and integration with Hadoop. The document then focuses on how SAP HANA enables smart data access and smart data integration across different data sources.
HTAP (Hybrid Transactional/Analytical Processing) databases allow both online transaction processing (OLTP) and online analytical processing (OLAP) to run simultaneously on the same data for real-time analytics. SAP HANA is an in-memory HTAP database that utilizes techniques like columnar storage and SIMD instructions to provide fast transactional processing and analytical queries on the same data. SAP HANA's lightweight locking mechanism and use of hardware transactional memory further improves the performance of OLTP workloads.
The document contains SQL statements and execution plans for counting records in a table where the ID is between 1 and 10 and the status is either '00' or '01'. It shows that for a status of '00' there are 10000 records, but for a status of '01' there are 0 records. Execution plans and statistics are provided with each statement to analyze the performance and resource usage.
The document contains log and monitoring data from an Oracle database. It includes statistics on CPU and disk usage, wait events, load averages, and a list of SQL statements with metrics like parse time, execute time, fetch time and row counts. Times are recorded from 23:48 to 23:49 and include usernames like SCOTT interacting with the database.
This document provides an overview of infrastructure automation tools like Chef, Puppet, Ansible, Serverspec, Infrataster and the Infrataster OracleDB plugin. It includes steps to setup the Oracle Instant Client, install necessary Ruby gems, write an Infrataster spec test to query the Oracle database and assert that the db_block_size parameter equals 8192, and execute the spec test with RSpec.
This document contains several database query results. The first result shows the database version and current user. Subsequent results show additional data from database tables, including column names and values like the database name, version number, and identifiers.
The document discusses SAP HANA, a platform for online transaction processing (OLTP) and online analytical processing (OLAP). It notes that SAP HANA allows for one copy of data to support both OLTP and OLAP workloads. It also discusses key capabilities of SAP HANA like advanced compression, multi-tenancy, and integration with Hadoop. The document then focuses on how SAP HANA enables smart data access and smart data integration across different data sources.
HTAP (Hybrid Transactional/Analytical Processing) databases allow both online transaction processing (OLTP) and online analytical processing (OLAP) to run simultaneously on the same data for real-time analytics. SAP HANA is an in-memory HTAP database that utilizes techniques like columnar storage and SIMD instructions to provide fast transactional processing and analytical queries on the same data. SAP HANA's lightweight locking mechanism and use of hardware transactional memory further improves the performance of OLTP workloads.
- SAP announced that over 18,000 customers are now running SAP HANA, the company's in-memory database platform. This represents a large increase in adoption of SAP HANA.
- Some of SAP's large customers implementing SAP HANA include Cisco, Siemens, VMware, Lidl, Heidelberg University Hospital, and others across various industries.
- SAP HANA is a key part of SAP's Modern Data Platform strategy to enable real-time analytics, advanced analytics, and digital transformation for customers.
The document discusses SAP HANA, express edition (HXE), a free software package that allows users to run an SAP HANA database on their local machine or cloud instance. It provides an overview of HXE's key capabilities and limitations, how to download, install, and manage an HXE system, and differences between the HXE server-only and full applications versions. Examples of using HXE administration and development tools like hdbsql and SAP HANA Studio are also provided.