Friday Apr 04, 2014

Oracle DB 12c runs best on Sparc

Oracle's vision of Engineered Systems is transforming into reality with every new product that Oracle is launching. Oracle Database 12c, which was launched in 2013, is an example on how Oracle software is optimized for Oracle Solaris SPARC. Oracle Database 12c is co-engineered with Solaris engineering team and Oracle’s world record SPARC T5 servers have best performance and maximum ROI.

Independent Software Vendors (ISV) who are developing applications using both Oracle DB 12c and Solaris are taking advantage of one core technology, one operating system, one virtualization tool for all the range of SPARC servers. An ISV application can boost its performance, flexibility and security just by using SPARC high numbers of cores and big memory, combined Oracle 12c/Solaris/SPARC multi-tenancy,  zones and LDoms light-weight virtualization technologies, SPARC and Solaris build-in encryption, etc.

Let’s take a look at how all this is translated into technical features. What makes Solaris and SPARC servers the best infrastructure for Oracle 12c enterprise databases?

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Monday Feb 24, 2014

LDom Direct-IO gives fast and virtualized IO to ECI Telecom

ECI Telecom is a leading telecom networking infrastructure vendor and a long-time Oracle partner. ECI provides innovative communications platforms and solutions to carriers and service providers worldwide, that enable customers to rapidly deploy cost-effective, revenue-generating services. ECI Telecom's Network Management solutions are built on the Oracle 11gR2 Database and Solaris Operating System.

"As one of the leading suppliers in the telecom networking infrastructure, ECI has a long term relationship with Oracle. Our main Network Management products are based on Oracle Database, Oracle Solaris and Oracle's Sun servers. Oracle Solaris is proven to be a mission critical OS for its high performance, extreme stability and binary compatibility guarantee."

Mark Markman, R&D Infrastructure Manager, ECI Telecom

Not long ago, ECI was asked by a customer to provide a scalable solution with a smaller footprint, with a preference for a VM-like environment that can (...)

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Thursday Oct 25, 2012

Morgan Stanley chooses Solaris 11 to run cloud file services

At the EAKC2012 Conference last week in Edinburg, Robert Milkowski, Unix engineer at Morgan Stanley, presented on deploying OpenAFS on Solaris 11. It makes a great proofpoint on how ZFS and DTrace gives a definite advantage to Solaris over Linux to run AFS distributed file system services, the "cloud file system" as Robert calls it in his blog. Robert used ZFS to achieve a 2-3x compression ratio on data and greatly lower the TCA and TCO of the storage subsystem, and DTrace to root-cause scalability bottlenecks and improve performance. As future ideas, Robert is looking at leveraging more Solaris features like Zones, ZFS Dedup, SSD for ZFS, etc.

Thursday Mar 29, 2012

Talend Enterprise Data Integration overperforms on Oracle SPARC T4

The SPARC T microprocessor, released in 2005 by Sun Microsystems, and now continued at Oracle, has a good track record in parallel execution and multi-threaded performance. However it was less suited for pure single-threaded workloads. The new SPARC T4 processor is now filling that gap by offering a 5x better single-thread performance over previous generations.

Following our long-term relationship with Talend, a fast growing ISV positioned by Gartner in the “Visionaries” quadrant of the “Magic Quadrant for Data Integration Tools”, we decided to test some of their integration components with the T4 chip, more precisely on a T4-1 system, in order to verify first hand if this new processor stands up to its promises.

Several tests were performed, mainly focused on:

  • Single-thread performance of the new SPARC T4 processor compared to an older SPARC T2+ processor
  • Overall throughput of the SPARC T4-1 server using multiple threads

The tests consisted in reading large amounts of data --ten's of gigabytes--, processing and writing them back to a file or an Oracle 11gR2 database table. They are CPU, memory and IO bound tests. Given the main focus of this project --CPU performance--, bottlenecks were removed as much as possible on the memory and IO sub-systems. When possible, the data to process was put into the ZFS filesystem cache, for instance. Also, two external storage devices were directly attached to the servers under test, each one divided in two ZFS pools for read and write operations.

Test Configuration

Multi-thread: Testing throughput on the Oracle T4-1

The tests were performed with different number of simultaneous threads (1, 2, 4, 8, 12, 16, 32, 48 and 64) and using different storage devices: Flash, Fibre Channel storage, two stripped internal disks and one single internal disk. All storage devices used ZFS as filesystem and volume management.

Each thread read a dedicated 1GB-large file containing 12.5M lines with the following structure:

1;Ronald;Reagan;South Highway;Santa Fe;Montana;98756;A;04-06-2006;09-08-2008
2;Theodore;Roosevelt;Timberlane Drive;Columbus;Louisiana;75677;A;10-05-2009;27-05-2008
3;Andrew;Madison;S Rustle St;Santa Fe;Arkansas;75677;A;29-04-2005;09-02-2008
4;Dwight;Adams;South Roosevelt Drive;Baton Rouge;Vermont;75677;A;15-02-2004;26-01-2007

The following graphs present the results of our tests:

Results 1

Unsurprisingly up to 16 threads, all files fit in the ZFS cache a.k.a L2ARC : once the cache is hot there is no performance difference depending on the underlying storage. From 16 threads upwards however, it is clear that IO becomes a bottleneck, having a good IO subsystem is thus key. Single-disk performance collapses whereas the Sun F5100 and ST6180 arrays allow the T4-1 to scale quite seamlessly. From 32 to 64 threads, the performance is almost constant with just a slow decline.

For the database load tests, only the best IO configuration --using external storage devices-- were used, hosting the Oracle table spaces and redo log files.

Results 2

Using the Sun Storage F5100 array allows the T4-1 server to scale up to 48 parallel JVM processes before saturating the CPU. The final result is a staggering 646K lines per second insertion in an Oracle table using 48 parallel threads.

Single-thread: Testing the single thread performance

Seven different tests were performed on both servers. Given the fact that only one thread, thus one file was read, no IO bottleneck was involved, all data being served from the ZFS cache.

  • Read File → Filter → Write File: Read file, filter data, write the filtered data in a new file. The filter is set on the “Status” column: only lines with status set to “A” are selected. This limits each output file to about 500 MB.
  • Read File → Load Database Table: Read file, insert into a single Oracle table.
  • Average: Read file, compute the average of a numeric column, write the result in a new file.
  • Division & Square Root: Read file, perform a division and square root on a numeric column, write the result data in a new file.
  • Oracle DB Dump: Dump the content of an Oracle table (12.5M rows) into a CSV file.
  • Transform: Read file, transform, write the result data in a new file. The transformations applied are: set the address column to upper case and add an extra column at the end, which is the concatenation of two columns.
  • Sort: Read file, sort a numeric and alpha numeric column, write the result data in a new file.

The following table and graph present the final results of the tests:

  • Throughput unit is thousand lines per second processed (K lines/second).
  • Improvement is the % of improvement between the T5140 and T4-1.


T4-1 (Time s.)

T5140 (Time s.)


T4-1 (Throughput)

T5140 (Throughput)







Read/Load Database












Division & Square Root






Oracle DB Dump


















Results 3

The improvement of single-thread performance is quite dramatic: depending on the tests, the T4 is between 5.4 to 7 times faster than the T2+. It seems clear that the SPARC T4 processor has gone a long way filling the gap in single-thread performance, without sacrifying the multi-threaded capability as it still shows a very impressive scaling on heavy-duty multi-threaded jobs.

Finally, as always at Oracle ISV Engineering, we are happy to help our ISV partners test their own applications on our platforms, so don't hesitate to contact us and let's see what the SPARC T4-based systems can do for your application!

"As describe in this benchmark, Talend Enterprise Data Integration has overperformed on T4. I was generally happy to see that the T4 gave scaling opportunities for many scenarios like complex aggregations. Row by row insertion in Oracle DB is faster with more than 650,000 rows per seconds without using any bulk Oracle capabilities !"

Cedric Carbone, Talend CTO.

Monday Mar 12, 2012

Mobile Tornado adopts Solaris features for better RAS and TCO

Mobile Tornado provides instant communication services for mobile devices, with a focus on enterprise workforce management. Its solutions include Push-To-Talk and Instant Locate, Alert & Message applications.

As a software developer, Mobile Tornado's main challenges are up-time --the applications are largely sold today into the homeland security and defense markets-- and scalability --during network peak usage. With these challenges in mind, and as part of the on-going engineering collaboration between Mobile Tornado and Oracle's ISV Engineering, we investigated which Oracle Solaris technologies would improve the application's availability and scalability while reducing the solution's TCO.

We looked at the following Oracle Solaris technologies: Solaris Cluster, ZFS and Zones.

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How open innovation and technology adoption translates to business value, with stories from our developer support work at Oracle's ISV Engineering.



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