It's here! Oracle Database In-Memory is officially released
By Maria Colgan on Jul 22, 2014
Oracle Database 12.1.0.2 was officially release today and is now available for download, which mean Oracle Database In-Memory is officially here!
Along with the software release comes a whole new set of collateral that explains in detail how all of the new Oracle Database In-Memory functionality works. The In-Memory page on Oracle.com has all of the juicy details including the official whitepaper.
Here is a quick look at the Introduction and the start of the paper. You can find the full paper here. Happy Reading!
Introduction
Today’s information architecture is much more dynamic than it was just a few years ago. Business users now demand more decision-enabling information, sooner. In order to keep up with increases in demand, companies are being forced to run analytics on their operational systems, in addition to their data warehouses. This leads to a precarious balancing act between transactional workloads, subject to frequent inserts and updates, and reporting style queries that need to scan large amounts of data.
With the introduction of Oracle Database In-Memory, a single database can now efficiently support mixed workloads, delivering optimal performance for transactions while simultaneously supporting real-time analytics and reporting. This is possible due to a unique "dual-format" architecture that enables data to be maintained in both the existing Oracle row format, for OLTP operations, and a new purely in-memory column format, optimized for analytical processing. In-Memory also enables both datamarts and data warehouses to provide more ad-hoc analytics, giving end-users the ability to ask multiple business driving queries in the same time it takes to run just one now.
Embedding the in-memory column format into the existing Oracle Database software ensures that it is fully compatible with ALL existing features, and requires no changes in the application layer. Companies striving to become real-time enterprises can more easily achieve their goals, regardless of what applications they are running. This paper describes the main components of Oracle Database In-Memory and provides simple, reproducible examples to make it easy to get acquainted with them. It also outlines how Database In-Memory can be integrated into existing operational systems and data warehouse environments to improve both performance and manageability.
With the introduction of Oracle Database In-Memory, a single database can now efficiently support mixed workloads, delivering optimal performance for transactions while simultaneously supporting real-time analytics and reporting. This is possible due to a unique "dual-format" architecture that enables data to be maintained in both the existing Oracle row format, for OLTP operations, and a new purely in-memory column format, optimized for analytical processing. In-Memory also enables both datamarts and data warehouses to provide more ad-hoc analytics, giving end-users the ability to ask multiple business driving queries in the same time it takes to run just one now.
Embedding the in-memory column format into the existing Oracle Database software ensures that it is fully compatible with ALL existing features, and requires no changes in the application layer. Companies striving to become real-time enterprises can more easily achieve their goals, regardless of what applications they are running. This paper describes the main components of Oracle Database In-Memory and provides simple, reproducible examples to make it easy to get acquainted with them. It also outlines how Database In-Memory can be integrated into existing operational systems and data warehouse environments to improve both performance and manageability.
Row Format vs. Column Format
Oracle Database has traditionally stored data in a row format. In a row format database, each new transaction or record stored in the database is represented as a new row in a table. That row is made up of multiple columns, with each column representing a different attribute about that record. A row format is ideal for online transaction systems, as it allows quick access to all of the columns in a record since all of the data for a given record are kept together in-memory and on-storage.
A column format database stores each of the attributes about a transaction or record in a separate column structure. A column format is ideal for analytics, as it allows for faster data retrieval when only a few columns are selected but the query accesses a large portion of the data set.
But what happens when a DML operation (insert, update or delete) occurs on each format? A row format is incredibly efficient for processing DML as it manipulates an entire record in one operation i.e. insert a row, update a row or delete a row. A column format is not so efficient at processing row-wise DML: In order to insert or delete a single record in a column format all of the columnar structures in the table must be changed.
Up until now you have been forced to pick just one format and suffer the tradeoff of either sub-optimal OLTP or sub-optimal analytics performance.
Oracle Database In-Memory (Database In-Memory) provides the best of both worlds by allowing data to be simultaneously populated in both an in-memory row format (the buffer cache) and a new in-memory column format.
A column format database stores each of the attributes about a transaction or record in a separate column structure. A column format is ideal for analytics, as it allows for faster data retrieval when only a few columns are selected but the query accesses a large portion of the data set.
But what happens when a DML operation (insert, update or delete) occurs on each format? A row format is incredibly efficient for processing DML as it manipulates an entire record in one operation i.e. insert a row, update a row or delete a row. A column format is not so efficient at processing row-wise DML: In order to insert or delete a single record in a column format all of the columnar structures in the table must be changed.
Up until now you have been forced to pick just one format and suffer the tradeoff of either sub-optimal OLTP or sub-optimal analytics performance.
Oracle Database In-Memory (Database In-Memory) provides the best of both worlds by allowing data to be simultaneously populated in both an in-memory row format (the buffer cache) and a new in-memory column format.
You can find the full paper here. Happy Reading!
