INTRODUCTION ASE 15.7
The market appeal and reach for Sybase ASE has dramatically increased with the 2010 acquisition of Sybase by SAP, the leader in business applications. SAP Business suite applications, as well as most all SAP applications running on SAP Netweaver technology, now run on Sybase ASE. These are indeed exciting times for Sybase ASE.
Sybase ASE 15.7 is the latest release in the ASE 15x product line; and it’s a feature-packed release. This document provides an overview of some of these new capabilities, and the benefits customers can expect from moving to ASE 15.7.
ASE 15.7 offers important enhancements for:
• Optimizing for Storage
• Application Developer Productivity
• Performance
• Enhanced Diagnostics & Monitoring
• Security Administration
OPTIMIZED FOR STORAGE Data growth is a serious challenge for enterprises. It can be attributed to a number of reasons: regulations requiring longer data retention, increased number of transactions, growth in unstructured data (images, text, audio and video), or the need to maintain data for longer periods of time for decision support systems. While disk itself has become cheaper, the growth in data continues to cause serious challenges for data centers.
The cost associated with data is not singular and limited to a single copy of the data. On the contrary, one unit of data on average translates into a minimum of 3-5 copies of it within the data center itself, as well as additional copies beyond the data center. Copies of the production data exist in development and testing systems, back-up and archived systems, secondary decision support systems as well as offsite backup and disaster recovery systems. Storage costs quickly get compounded when hardware costs, software license costs, data center floor space and power consumption costs, data transfer and bandwidth costs, and labor costs are thrown into the overall cost of maintaining this data. Clearly the oft-heard refrain "disk is cheap" can only be stretched so far before costs start piling up.
And this does not even consider performance costs due to I/O demands and cache memory requirements when processing this data!
ASE 15.7 introduces the following to help reduce storage requirements:
Compression
• Compression: Regular data and LOBs
• In-row LOBs
• Create nonmaterialized non-NULL columns without data copy
• Ability to shrink the transaction log
In prior releases ASE customers had the ability to compress backups thus helping reduce offline storage costs. ASE 15.7 now allows in-database compression for active data sets. Both regular relational data as well as unstructured data (large objects or LOBs) can be compressed. Early internal benchmarks indicate that compression ratios can readily hit the 50-80%.
ASE 15.7 uses a number of compression strategies to achieve high compression ratios. This includes compression within a single row to compress away empty spaces/zeroes in fixed length columns. At a page/block level this includes both page dictionary and page index compression strategies. Repeated data items as well as repeated sets of data items are replaced by a single reference resulting in dramatic savings for duplicated data. Data can be compressed at database, table or partition level. This allows for customers to separately make compression choices for active or inactive data.
ASE 15.7 also supports in-database LOB compression. Given that LOBs can be very large in size (up to 2GB), compression can result in very significant space savings. FastLZ and ZLib compression techniques are supported, which are lossless compression algorithms. While the former provides lower CPU usage and execution times, the latter provides higher compression ratios.
Customers have the flexibility to choose LOB compression at database, table or column level.
In-Row LOBs
Modern applications increasingly need to manage and manipulate unstructured data. This data is stored as LOB columns (e.g. text, images, unitext, XML). LOBs can vary in size from a few bytes to gigabytes. ASE optimized for LOB storage by allocating separate storage blocks that could be pointed to from the parent data row. This was very efficient for handling larger LOBs. ASE 15.7 enhances this capability by now also supporting in-row LOBs for the situations when LOBs are fairly small and can readily fit within the parent row.
This has two advantages: storage savings by optimizing for the space allocated for small LOBs, as well as performance benefits for retrieval of small LOBs by reducing the I/O overhead.
ASE seamlessly handles the migration of LOBs from in-row to off-row storage (or vice versa) to always optimize for the storage required as LOBs change in size due to updates.
ASE 15.7 allows for the ability to shrink a transaction log. Transaction logs can often grow very large due to a number of reasons: enlarged to handle log-full situations, to support one-time operations that may require lots of space or even due to generous estimates during capacity planning.
APPLICATION DEVELOPER PRODUCTIVITY
ASE 15.7 offers numerous enhancements designed to enhance the productivity of application developers. These include:
• Simpler and more efficient LOB retrieval and manipulation
• Greater flexibility around concurrency and isolation levels
• Enhanced SQL expressiveness
• Support for scripting language drivers
A number of T-SQL commands are provided to work with LOBs. These commands allow easy manipulation of LOBs (truncation and concatenation of LOBs, overwriting portions of a LOB, extracting substrings in a LOB, and so on). ODBC clients can use these T-SQL commands to manipulate LOBs. The jConnect JDBC driver supports access to the locators using Blob, Clob and NClob classes.
In addition to the above, LOBs can now also be passed as parameters to stored procedures. This adds greater flexibility to manipulate LOBs within stored procedures and reduces code complexity for developers.
ASE 15.7 also provides a number of T-SQL updates that allow for greater SQL expressiveness as well as control over concurrency and isolation level semantics. Some of these include:
Non-materialized Non-NULL Columns Without Data Copy
In the past adding non-NULL columns to an existing table required a complete data copy. This can be particularly cumbersome for very large tables. ASE 15.7 now allows creation of non-materialized non-NULL columns. This means columns get created without actually making a data copy (which can require a large amount of temporary space for the data copy, equal to the original table size). This saves both space and time.
When such rows are actually updated they get instantiated (physically stored in the row) behind the scenes.
Shrinking Transaction Log• Support for MERGE statement to allow for transferring rows from a source table (table, view derived table) into a target table.
• SELECT FOR UPDATE to allow selected rows to be locked for a later update
• Ability to release read cursor locks at cursor close for active transactions for all isolation levels
• Various nested select statement enhancements
• Ability to run all system procedures and select DDLs in chained transaction mode
ENHANCED DIAGNOSTICS & MONITORING
ASE 15.7 provides numerous enhancements around diagnostics and monitoring. Some of these include: SECURITY ADMINISTRATION
• Ability to save abstract plan information in the statement cache
• Ability to output cached plan in XML
• Ability to analyze dynamic parameters before running a query which can help to avoid inefficient query plans
• Ability to monitor lock timeouts
• Ability to display statistics and histograms for various objects, via a system procedure (T-SQL equivalent of the standalone
• Ability to monitor cursor statements• Ability to analyze the query plan generated to understand the various factors behind ASE’s choice of the query plan
ASE 15.7 also introduced the Several security improvements are introduced in ASE 15.7. These include:
• Object ownership change
• Support for login profiles
• Split knowledge/Dual control for protecting encryption keys (a requirement for the payments card industry data standard, PCI-DSS)
• Improved encryption for FIPS 140-2 compliance — encrypting role passwords with SHA256, and encrypting external server passwords and hidden SQL text with AES256
• Single sign-on and end to end Kerberos credential forwarding
ASE 15.7 introduces the ability to conveniently change object ownership.
Another powerful feature that allows for easy security administration is the support for login profiles. Before ASE 15.7 each ASE login had to be managed individually. This can be cumbersome and makes it difficult to implement changes in policies that often affect large number of users.
ASE 15.7 introduces the login profiles which are SQL-defined attribute containers of login characteristics and their values (such as default database, login script, auto activated roles, authenticate with). Groups of logins can share login profiles. These are easy to administer and provide flexibility to implement security policies and comply with changing regulations.PERFORMANCE ENHANCEMENTS
ASE 15.7 focuses on two specific areas for performance: fetch statements, as well as ability to cache cursor query plans in the statement cache. optdiag utility)sp_opt_querystats system procedure)
• Reducing query latency, especially for dynamic SQL
• ASE kernel updates to better utilize parallel hardware
ASE 15.7 also provides an updated kernel that can better leverage parallel hardware. The kernel updates enhance ASE scalability on systems with very large number of processors, processor cores, and hardware threads. Updates also provide better integration of I/O event processing and reduce I/O overhead within the ASE server. These enhancements will not only improve I/O performance but also help with operation of ASE in virtualized environments.
The market appeal and reach for Sybase ASE has dramatically increased with the 2010 acquisition of Sybase by SAP, the leader in business applications. SAP Business suite applications, as well as most all SAP applications running on SAP Netweaver technology, now run on Sybase ASE. These are indeed exciting times for Sybase ASE.
Sybase ASE 15.7 is the latest release in the ASE 15x product line; and it’s a feature-packed release. This document provides an overview of some of these new capabilities, and the benefits customers can expect from moving to ASE 15.7.
ASE 15.7 offers important enhancements for:
• Application Developer Productivity
• Performance
• Enhanced Diagnostics & Monitoring
• Security Administration
OPTIMIZED FOR STORAGE
The cost associated with data is not singular and limited to a single copy of the data. On the contrary, one unit of data on average translates into a minimum of 3-5 copies of it within the data center itself, as well as additional copies beyond the data center. Copies of the production data exist in development and testing systems, back-up and archived systems, secondary decision support systems as well as offsite backup and disaster recovery systems. Storage costs quickly get compounded when hardware costs, software license costs, data center floor space and power consumption costs, data transfer and bandwidth costs, and labor costs are thrown into the overall cost of maintaining this data. Clearly the oft-heard refrain "disk is cheap" can only be stretched so far before costs start piling up.
And this does not even consider performance costs due to I/O demands and cache memory requirements when processing this data!
ASE 15.7 introduces the following to help reduce storage requirements:
Compression
• Compression: Regular data and LOBs
• In-row LOBs
• Create nonmaterialized non-NULL columns without data copy
• Ability to shrink the transaction log
In prior releases ASE customers had the ability to compress backups thus helping reduce offline storage costs. ASE 15.7 now allows in-database compression for active data sets. Both regular relational data as well as unstructured data (large objects or LOBs) can be compressed. Early internal benchmarks indicate that compression ratios can readily hit the 50-80%.
ASE 15.7 uses a number of compression strategies to achieve high compression ratios. This includes compression within a single row to compress away empty spaces/zeroes in fixed length columns. At a page/block level this includes both page dictionary and page index compression strategies. Repeated data items as well as repeated sets of data items are replaced by a single reference resulting in dramatic savings for duplicated data. Data can be compressed at database, table or partition level. This allows for customers to separately make compression choices for active or inactive data.
ASE 15.7 also supports in-database LOB compression. Given that LOBs can be very large in size (up to 2GB), compression can result in very significant space savings. FastLZ and ZLib compression techniques are supported, which are lossless compression algorithms. While the former provides lower CPU usage and execution times, the latter provides higher compression ratios.
Customers have the flexibility to choose LOB compression at database, table or column level.
In-Row LOBs
Modern applications increasingly need to manage and manipulate unstructured data. This data is stored as LOB columns (e.g. text, images, unitext, XML). LOBs can vary in size from a few bytes to gigabytes. ASE optimized for LOB storage by allocating separate storage blocks that could be pointed to from the parent data row. This was very efficient for handling larger LOBs. ASE 15.7 enhances this capability by now also supporting in-row LOBs for the situations when LOBs are fairly small and can readily fit within the parent row.
This has two advantages: storage savings by optimizing for the space allocated for small LOBs, as well as performance benefits for retrieval of small LOBs by reducing the I/O overhead.
ASE seamlessly handles the migration of LOBs from in-row to off-row storage (or vice versa) to always optimize for the storage required as LOBs change in size due to updates.
ASE 15.7 allows for the ability to shrink a transaction log. Transaction logs can often grow very large due to a number of reasons: enlarged to handle log-full situations, to support one-time operations that may require lots of space or even due to generous estimates during capacity planning.
APPLICATION DEVELOPER PRODUCTIVITY
ASE 15.7 offers numerous enhancements designed to enhance the productivity of application developers. These include:
• Greater flexibility around concurrency and isolation levels
• Enhanced SQL expressiveness
• Support for scripting language drivers
A number of T-SQL commands are provided to work with LOBs. These commands allow easy manipulation of LOBs (truncation and concatenation of LOBs, overwriting portions of a LOB, extracting substrings in a LOB, and so on). ODBC clients can use these T-SQL commands to manipulate LOBs. The jConnect JDBC driver supports access to the locators using Blob, Clob and NClob classes.
In addition to the above, LOBs can now also be passed as parameters to stored procedures. This adds greater flexibility to manipulate LOBs within stored procedures and reduces code complexity for developers.
ASE 15.7 also provides a number of T-SQL updates that allow for greater SQL expressiveness as well as control over concurrency and isolation level semantics. Some of these include:
Non-materialized Non-NULL Columns Without Data Copy
In the past adding non-NULL columns to an existing table required a complete data copy. This can be particularly cumbersome for very large tables. ASE 15.7 now allows creation of non-materialized non-NULL columns. This means columns get created without actually making a data copy (which can require a large amount of temporary space for the data copy, equal to the original table size). This saves both space and time.
When such rows are actually updated they get instantiated (physically stored in the row) behind the scenes.
Shrinking Transaction Log
• SELECT FOR UPDATE to allow selected rows to be locked for a later update
• Ability to release read cursor locks at cursor close for active transactions for all isolation levels
• Various nested select statement enhancements
• Ability to run all system procedures and select DDLs in chained transaction mode
ASE 15.7 provides numerous enhancements around diagnostics and monitoring. Some of these include:
• Ability to output cached plan in XML
• Ability to analyze dynamic parameters before running a query which can help to avoid inefficient query plans
• Ability to monitor lock timeouts
• Ability to display statistics and histograms for various objects, via a system procedure (T-SQL equivalent of the standalone
• Ability to monitor cursor statements• Ability to analyze the query plan generated to understand the various factors behind ASE’s choice of the query plan
ASE 15.7 also introduced the
• Support for login profiles
• Split knowledge/Dual control for protecting encryption keys (a requirement for the payments card industry data standard, PCI-DSS)
• Improved encryption for FIPS 140-2 compliance — encrypting role passwords with SHA256, and encrypting external server passwords and hidden SQL text with AES256
• Single sign-on and end to end Kerberos credential forwarding
ASE 15.7 introduces the ability to conveniently change object ownership.
Another powerful feature that allows for easy security administration is the support for login profiles. Before ASE 15.7 each ASE login had to be managed individually. This can be cumbersome and makes it difficult to implement changes in policies that often affect large number of users.
ASE 15.7 introduces the login profiles which are SQL-defined attribute containers of login characteristics and their values (such as default database, login script, auto activated roles, authenticate with). Groups of logins can share login profiles. These are easy to administer and provide flexibility to implement security policies and comply with changing regulations.
ASE 15.7 focuses on two specific areas for performance: fetch statements, as well as ability to cache cursor query plans in the statement cache. optdiag utility)sp_opt_querystats system procedure)
• ASE kernel updates to better utilize parallel hardware
ASE 15.7 also provides an updated kernel that can better leverage parallel hardware. The kernel updates enhance ASE scalability on systems with very large number of processors, processor cores, and hardware threads. Updates also provide better integration of I/O event processing and reduce I/O overhead within the ASE server. These enhancements will not only improve I/O performance but also help with operation of ASE in virtualized environments.
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