Analytic Workloads on Oracle and ParAccel

Transcription

1 Analytic Workloads on Oracle and ParAccel Head-to-head comparisons of real-world analytic workloads demonstrate the performance improvement and cost savings of ParAccel over Oracle. ParAccel was designed from the ground up for analytic performance. Moving analytic workloads off an Oracle data warehouse and onto ParAccel s analytic platform frees up valuable data warehouse resources and allows highly-paid business analysts to do what they were hired to do ParAccel, Inc. All Rights Reserved. ParAccel product names are trademarks of ParAccel, Inc. Other product names are trademarks of their respective owners.

2 Executive Summary As today s business leaders increasingly discover the insights and advantages of big data analytics, they push their companies to become more data-centric and analyticsdriven. Companies hire business analysts to explore the outer bounds of these analytics advantages, but they quickly learn that legacy data warehouses systems like Oracle severely restrict their ability to provide value to the company. ParAccel offers the Analytic Offload solution, which seamlessly moves complex analytic workloads off of Oracle, and onto a platform specifically designed to deliver unconstrained analytics. This relieves pressure on the company s existing Oracle infrastructure while simultaneously providing business analysts with the tools and data access they need to do their jobs.instead of working with sampled or aggregated data, or spending hours and days waiting for access, analysts are free to explore big data in ways that can unearth new insights and drive new competitive advantages. In real-world customer comparisons with both Oracle s legacy data warehouse solution and newer Exadata platform, ParAccel demonstrates dramatic advantages in all phases of typical big data analytics work, including administration, loading, building, performance, and analyst productivity, which all leads to a lower total cost of ownership and increased value for the business. Data Warehouse Overload and Analytic Constraints Today s companies have access to data that is increasingly complex, widely varied in form, and available in volumes that would have been considered absurd just five years ago. Additionally, the concurrent development of more sophisticated data-capture systems and cheaper storage has given rise to a growing business appetite for the insights this big data can provide. However, in most cases, legacy Oracle data warehouses are not able to keep up with the needs of the analytics-driven enterprise. Oracle was conceived and developed when the largest databases in the world rarely exceeded a few gigabytes. It is, by design, a database meant for transaction processing. The features which it has deployed in the last decade to address data warehousing needs, and in particular the Exadata platform, represent Oracle s attempt to extend a legacy transaction processing engine into a big data analytics platform. Today, the internals of an Oracle database are a clutter of tables, partitions, indexes, materialized views, queues, system objects, caches, and more; all of which must be maintained by a high-cost, specially-trained team of DBAs. Even purchasing the software requires navigating a morass of high-priced options and add-ons which certainly confuse in fact, if not by design. Developing new functionality requires a major investment of time and effort to mitigate poor performance. Similarly, modifying existing functionality is a costly, high-risk exercise fraught with risks and challenges due to the constant workarounds Oracle must engineer into the database in its attempt to stay competitive in the big data space. By way of example, one customer now using ParAccel reported that after the migration, an Oracle process which previously took 46 hours completed in just 30 seconds in ParAccel. At the same time, they were able to redeploy the DBA team to higher-value activities, reducing the DBA time burden from 6 full-time employees (FTEs) to one-half of an FTE. For more information, visit ParAccel.com/technology or contact us at

3 They also were able to reduce their ETL volume by half. Because the ParAccel platform was so much more efficient, they were able to deploy 20 times as much data to their analysts, changing the analytics game for the entire company. The typical result for a company using Oracle today is that Oracle data warehouses constantly operate under overload conditions. Input overload occurs when information technology teams are continuously bombarded with requests to integrate new data types or more detailed data. Output overload happens as the appetite for business intelligence and reporting expands. Companies run scheduled reports, enterprise-wide dashboards, and full-scan queries, but then they also want to add access for analytics teams to perform increasingly complex and nuanced data work. For legacy data warehouse systems like Oracle, the input and output overload contribute to the more pernicious problem of resource and administrative overload. A data warehouse that is being pushed to its limit creates a resource drain that quickly becomes prohibitive. It takes time, money, and man-hours to model data, manage workloads, load data, create indexes, and adjust optimizations. In-house experts or outside consultants must constantly tune the Oracle platform to enable the most basic analytics demanded by the business. Even if a company decides to expand their Oracle database, the cost of a bigger data warehouse quickly exceeds the increased benefit the company is able to achieve. Analytic workloads require administrative resources far beyond the requirements of reporting and dashboards. Given the iterative nature of analytics work, every change in an algorithm or addition of data means compounded administrative overhead for a legacy data warehouse. With the data warehouse on overload, companies force their analysts to use sampled data or aggregated data, thus hampering both the analytic process and the quality of results. Alternatively, some choose to severely restrict analyst access to the data. One company using Oracle for their data warehouse reported that their business analysts were productive with only 10-20% of their time. The remaining 80-90% of their time was spent gathering data and waiting for queries to run on an overloaded platform. These coping strategies introduce constraints to the analytic process that severely hinder a company s ability to make the best use of their data. When they limit their analysts so that they can work with data on legacy Oracle systems, the promise of big data analytics breaks down. Then, companies are forced to compromise on their vision of what an analytics program can do for their business. 3

4 Benefits of ParAccel s Analytic Offload Solution Several major organizations have deployed the ParAccel Analytic Platform alongside their legacy Oracle systems. This allows companies to take advantage of ParAccel s superior analytics performance, without disrupting their existing Oracle environment. The ParAccel implementations have yielded a number of advantages that can be summed up in the experience of unconstrained analytics. Reduction in Database Administration Requirements The ParAccel platform requires no database tuning, and only very minimal modeling work. On Oracle, one large retailer s database administrators typically spent upwards of 50 hours modeling the data, building indices, creating views, and iteratively tuning performance on specific queries and reports. The comparable time on the ParAccel platform was a single hour, as there was no need to redefine a schema or tune the database for performance. Accelerated Analytic Performance Other customers, particularly in the retail space, report similar experiences. Retailers run very complex, data-intensive analytics such as market basket analysis and shrink processing. These analytics are core to the business because they drive pricing, promotions, inventory, distribution, bundling, assortment, store operations and more. For one retailer, a market basket report was taking seven hours to run in Oracle. It ran in 1 minute and 15 seconds on ParAccel. A shrink processing query was taking 46 hours to run in Oracle. It ran in 30 seconds on ParAccel with no tuning, no indexing, and no special preparation. The retailer simply loaded the data and ran the query. This type of extreme performance acceleration is a fairly typical result for complex queries that are moved from Oracle to ParAccel. Faster Time to Analytic Productivity In another case, a multi-dimensional report required five hours to load data and create indexes. The company moved this report to ParAccel, because the platform s analytics engine operates on a columnar database and is schema-neutral, and so has no need for indexing. In addition, data loading in ParAccel s platform runs quickly, as it is done in parallel on a multi-parallel processing (MPP) architecture. As a result the five-hour Oracle load and build window was reduced to 45 seconds on ParAccel. Increased Business Analyst Utilization Companies have also appreciated keeping analysts focused on analysis not data management. When they were trying to deploy their analytics program on the Oracle data warehouse, a large retailer s business analysts spent 80-90% of their time gathering data and waiting for access to the system. With ParAccel, the analyst s productivity has gone to nearly 100% focused on strategic activities, as they no longer are constrained by Oracle s limitations. They are free to run their complex analytics in ParAccel while the company s use of the Oracle platform remains intact for enterprise reporting. Lower Infrastructure Costs ParAccel typically achieves a 10 to 20 times performance increase, while reducing data storage needs. This lowers the cost of the server, storage, and networking infrastructure required to support analytics. In addition, compared to Oracle Exadata, ParAccel provides a significant performance increase and eases data center deployment by running on industry-standard hardware or in the cloud. There is no need to buy specialized Oracle hardware appliances, interrupting the push toward a standards-based data center. 4

5 Lower Storage Requirements Organizations have also lauded ParAccel s significant data compression advantages due both to its columnar orientation and adaptive compression technology. A recent customer experience showed that the data in a 10-terabyte Oracle database compressed down to only 800 gigabytes in ParAccel. Increased Opportunity for Innovation The ParAccel solution supports greater levels of innovation compared to an Oracle data warehouse, because of increased analytic capabilities, higher performance and lower costs. This enables companies to focus on analytics, expanding their programs in unique ways that weren t previously possible. One organization replicated their ParAccel instance to create a new analytic sandbox where analysts can explore, experiment, and even upload their own data to provide new perspectives. Seamless Integration to Existing Infrastructure ParAccel s platform can complement existing Oracle environments, enabling new analytic capabilities while the existing data infrastructure continues to operate. ParAccel has developed On-Demand Integration (ODI) modules that allow analysts to combine ParAccel data with Oracle data, or other data sources including Teradata and Hadoop. Better yet, using ParAccel, analysts can pull the data whenever they need it, right at the point they execute a query, without upfront data preparation. The ability for analysts to have inline access to streaming data, operational databases and non-relational data, along with data already stored in ParAccel, enables easy access to new data sources without major integration projects. Migrate Workloads to the Most Suitable Platform As demonstrated by real-world metrics, ParAccel s Analytic Offload solution seamlessly moves complex analytic workloads off of Oracle and onto a high-performance platform, purpose-built and designed for analytics. At a fraction of the cost compared to an Oracle expansion, this offload strategy provides business analysts with the freedom they need to unlock value from data while also relieving pressure on the company s existing Oracle infrastructure. Then, the Oracle data warehouse is once again free to do what it does best, while the analyst can operate in an environment of unconstrained analytics, helping the organization truly become an analytic-driven enterprise. For more information, visit or call your local sales director. ParAccel can also be reached at