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Leveraging Big Data with Hadoop, NoSQL and RDBMS

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Hadoop and NoSQL databases have emerged as leading choices by bringing new capabilities to the field of data management and analysis. At the same time, the RDBMS, firmly entrenched in most enterprises, continues to advance in features and varieties to address new challenges.

Join us for a special roundtable webcast on April 7th to learn:

The key differences between Hadoop, NoSQL and RDBMS today
The key use cases
How to choose the best platform for your business needs
When a hybrid approach will best fit your needs
Best practices for managing, securing and integrating data across platforms

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Leveraging Big Data with Hadoop, NoSQL and RDBMS

  1. 1. Leveraging Big Data with Hadoop, NoSQL and RDBMS — April 7, 2016 Brian Bulkowski
  2. 2. 2Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ] Sustainable Differentiators SPEED AT SCALE • Index in RAM, Data in Flash: Persistence • Key-value store • Open Source SMART CLIENTS • Ease of use for programmers • Patented functionality that accelerates development by shielding developers from low level programming CLUSTERING • Availability • Patented clustering algorithms that solve the hardest problems of distributed computing TCO • Optimized for Flash • Demonstrated 10 to 1 price performance savings • Battle tested, almost no downtime
  3. 3. 3Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ] 10X Faster or 10X Fewer
  4. 4. 4Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ] Polyglot Architecture Transactions (Compliance, Legacy) (Oracle, DB/2, SQLServer, MariaDB, Postgres) Operational In-memory (Fast, Scalable, HA) (Aerospike, Cassandra with Cache, Coherence) Operational Analytics Relational Ad-Hoc (Exadata, Aster, Teradata) Hadoop Big Data (Cloudera, Hortonworks, MapR) Column (Vertica, RedShift, SnowFlake, Oracle) Graph (Neo4J, Objectivity, ... ) Streaming (Spark, Heron) … fast analytics but still analytics App server architecture In-memory SQL (VoltDB, MemSQL, …) Polyglot Analytics systems (multiple are required because of performance reasons –data layout matters) Operational In-memory Read Write
  5. 5. 5Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ] Old Style Architecture Has Significant Limitations Challenges • Complex • Maintainability • Durability • Consistency • Scalability • Cost ($) • Data Lag Caching Layer Operational Database Real-time Consumer Facing Pricing / Inventory/Billing Real-time Decisioning Streaming Data Legacy Database (Mainframe) RDBMS Databas e Transactional Systems Enterprise Environment Legacy RDBMS HDFS BASED
  6. 6. 6Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ] High Performance NoSQL Enables Real-time Applications Real-time Consumer Facing Pricing / Inventory/Billing Real-time Decisioning Streaming Data Aerospike Connectors Legacy Database (Mainframe) RDBMS Databas e Transactional Systems Enterprise Environment XDR Aerospike Legacy RDBMS HDFS BASED Next Generation Operational Database Business transactions of 500/sec X 2500 reads/writes/ calculations per business transaction = 1.25M Server Transactions/sec Speed at Scale, Predictable Performance, Highest Availability & Lowest TCO
  7. 7. 7Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ] Business Challenge • Meet SLAs of 750 ms per business transaction • Differentiate between fraudulent and legitimate orders in real- time • Support next-generation Machine Learning • Stop loss of business due to latency • Support hundreds of DB reads/writes per credit card transaction • Increase operational data 10x Prevent Only Fraudulent Transactions
  8. 8. 8Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ] Selected Aerospike in-Memory NoSQL • Built for Flash • Predictable Low latency at High Throughput • Immediate consistency, no data loss • Cross data center (XDR) support • 20 Server Cluster • Dell 730xd w/ 4NVMe SSDs Prevent Only Fraudulent Transactions Credit Card Processing System Fraud Detection & Protection App Rules Rule 1 Rule 2 Rule 3 Historical Data Rule 1-Passed Rule 2-Passed Rule 3-Failed Account Behavior Static Data Account Statistics
  9. 9. 9Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ] Intra-day System of Record Challenge • DB2 (RDBMS) stores positions for 10 Million customers • Must update stock prices, show balances on 300 positions, process 250M transactions, 2M updates/day • Risk, System of Engagement and Mobile • Data inconsistencies, long restarts, growing number of servers, restarts take 1 hour
  10. 10. 10Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ] Intra-day System of Record Selected Aerospike in-Memory NoSQL • Built for Flash • Predictable Low latency at High Throughput • Immediate consistency, no data loss • Hot standby implementation for extra redundancy • Cross data center (XDR) support • 10 Server Cluster IBM DB2 (Mainframe) Real-Time App Record App Finance App Real-Time Data Feed Start of the Day Data Loading End of Day Reconciliation Account Positions
  11. 11. 11Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ] AdTech – Predictive Analytics at Scale Challenge • Low read latency (milliseconds) • 100K to 5M operations/second • Ensure 100% uptime • Provide global data replication Performance achieved • 1 to 6 billion cookies tracked • 5.0M auctions per second • 100ms ad rendering, 50ms real-time bidding, 1ms database access • 1.5KB median object size Selected Aerospike NoSQL over competition • 10X fewer nodes • 10X better TCO • 20X better read latency • High throughput at low latency Ads is Displayed Publishers Ad Networks & SSPs Ad Exchanges Demand Side Platform Data Management Platforms Brands Agencies Buyers 0 ms 100 ms
  12. 12. 12Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ] Telco – Real-Time Billing and Charging Systems Challenge • Edge access to regulate traffic • Accessible using provisioning applications (self-serve and through support personnel) Need for extremely high availability, reliably, low latency • > TBs of data • 10-100M objects • 10-200K TPS Selected Aerospike in-Memory NoSQL • Clustered system • Predictable low latency at high throughput • Highly-available and reliable on failure • Cross data center (XDR) support SOURCE DEVICE/USER DESTINATIONReal-Time Auth. QoS Billing Request Execute Request Real-Time ChecksConfig Module App Update Device User Setting Hot-Standby XDR
  13. 13. THANK YOU! www.aerospike.com/quick-start/ Email Info@Aersopike.com @aerospikedb #Aerospike

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