Solution Brief Run your Data Warehouse Applications At the Speed of Memory Highlights Simplify Data Warehouse Environments • Speed up reporting times by removing stages in the batch process • Eliminate the need for production copy data marts • Reduce storage overprovisioning To better enable decision makers in an era of data overload, the mandate today is the ability to run ad hoc, dynamic queries, where reports can be generated in real-time, anytime to gain business or financial insights. To gain valuable real-time business insights from data volumes, storage solutions need to be more predictable in their performance behavior as well as scale cost-effectively. Challenges with Existing Data Warehouse Environments Data warehouses ingest data from multiple sources and then transform them into meaningful data sets for consumption. Data is loaded, updated, changed and accessed throughout the day. A typical datawarehouse comprises of various steps including importing, staging, transformation, integration, sorting. Therefore, the challenges for datawarehouse systems are multi-fold: • Time consuming and complicated datawarehouse processes are difficult to manage and support and take too long to run Accelerate Data Transformations (ETL) • Legacy storage with slow performance is limiting the move towards real-time analytics • Up to 20x increase in ETL performance • Secondary copies for reporting (data marts) are used to protect the performance and integrity of production, leading to storage inefficiencies and data replication complexity. • Make data available faster and improve user experience Working through the time-consuming data warehouse steps may require multiple copies of data. When doing transformations or sorting, the application might be creating a new dataset while retaining the raw data, storing multiple copies of the same data in the staging area. This results in storage being overprovisioned but only used during the batch process. • Up to 20x faster report generation • Sub-millisecond latency for any workload Lower Total Cost of Ownership • Reduced operational and capital expenses The Violin Flash Memory Array Difference The value in data warehouse lies in the ingress and egress of terabytes of data – data coming from the database and data expelled to the database for consumption – as well as the administration of the data over time. Most businesses will batch up jobs into overnight activities so as to not impact production, but in reality, these batch processes take hours to complete with the risk that running into the next working day’s activities can cause a massive performance and financial hit. • Up to 80% reduction in power, cooling, space costs • Lower data locality management software licensing VMEM.COM ©2013 Violin Memory, Inc. All rights reserved. These products and technologies are protected by U.S. and international copyright and intellectual property laws. Violin Memory is a registered trademark of Violin Memory, Inc. in the United States and/or other jurisdictions. Solution Brief: Run your Data Warehouse Applications At the Speed of Memory Flash Speeds Up the Transaction Processes, Enabling Real-time Reporting Flash storage provides maximum raw, random I/O performance with very low microsecond latency under any workload. The distributed block nature of Violin’s flash Arrays allow for massive parallelism, resulting in faster and more stable throughput of data. Sustained microsecond latency allows for fast data and log writing producing 5-10x faster load times. The natural fragmentation of data in data warehouse environments is irrelevant to Violin’s unique, distributed architecture, therefore data loads can be reduced in complexity by dropping the sort and single-threaded write processes. With Violin, an ETL can be a full blast of data utilizing all cores straight into the final partition or table, instead of having to sequentially sort the data and sequentially write it out to the physical storage. Violin’s faster read/write latencies also allow for quicker sorting, ordering and temp space utilization, providing for overall quicker report run durations. Its distributed architecture allows for maximum concurrency. All memory addresses are equally accessible at the same speed at all times so that any number of concurrent users can access data without degrading storage performance. Data warehouse processes on Violin flash Memory Arrays can thus be reduced to the following: Staging Table (ETL) Main Table Source-1 Source-2 Source-3 Ready immediately! Source-n By removing the layers of the batch process required to make reports perform well on traditional disks, the overall time taken from ingest to egress is dramatically reduced on Violin’s flash Arrays, at reduced complexity. An 8-hour overnight batch process can be achieved in 30-60 minutes. Flash Simplifies Data Warehouse Administration Violin’s distributed architecture allows for any number of LUNS to run at the same speed. The same distributed architecture removes the concept of hot spots or issues pertaining to data locality, therefore, you do not need expensive or time-requiring software to distribute hot data, run tiering or otherwise manage issues pertaining to data locality. Violin arrays engage all flash at all times in order to increase parallelization and engage as many flash chips as possible for maximum speed, at all times. Storage tasks such as backups and archives are magnitudes faster and can be ran concurrently, without impact. Violin’s unique and dynamic all-flash, all-silicon, parallelized array enables data warehouse applications to be predictable in their performance and linearly scalable, at a lower TCO than traditional disk-based storage. Violin Memory, Inc. 685 Clyde Ave, Mountain View, CA 94043 Ph: 1-888-9VIOLIN (984-6546) E-mail: [email protected] vmem-13q2-sb-datawarehouse-usltr-en-r01 vmem-12q4-sb-oracledb-uslet-en-r2-print