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Getting Started with Apache Ignite as a Distributed Database

In-Memory Computing Meetup Vol.1, Tokyo, May 23

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Getting Started with Apache Ignite as a Distributed Database

  1. 1. Getting Started with Apache Ignite as a Distributed Database Stephen Leung Director of Solution Architect, Asia Pacific 2019 © GridGain Systems
  2. 2. 2018 © GridGain Systems Agenda • Why not standard RDBMS and NoSQL? • Apache Ignite Overview • Reference Case sharing • Q & A
  3. 3. 2018 © GridGain Systems Why not Standard RDBMS and NoSQL?
  4. 4. 2018 © GridGain Systems Existing Databases are Too Slow
  5. 5. 2018 © GridGain Systems Existing Databases Can't Scale
  6. 6. 2018 © GridGain Systems Existing Databases Can't Scale
  7. 7. 2018 © GridGain Systems NoSQL to the Rescue?
  8. 8. 2018 © GridGain Systems NoSQL to the Rescue? RDBMS Consistent, but not scalable NoSQL Scalable, but not consistent
  9. 9. 2018 © GridGain Systems Apache Ignite Consistent & Scalable
  10. 10. 2018 © GridGain Systems Ignite Data Warehouse Operational DB TransactionsAnalytics, ML, AI ETL Analytics, ML, AI & Transactions Real Time, Scalable, Available, Flexible ETL, Batch, Inflexible HTAP Architecture
  11. 11. 2018 © GridGain Systems In-Memory Computing Mainframe NoSQL Hadoop Data Layer RDBMS In-Memory Computing Financial Services Initiatives Private/Public Cloud/SaaS Regulatory Compliance Omnichannel Banking Security Fraud Risk Management Trading HPC
  12. 12. 2018 © GridGain Systems Current solution comparison Feature In-Memory Cache (Redis) IMDG (Hazelcast, GigaSpaces) IMDB (MemSQL, VoltDB) IMC Platform (GridGain) Scale Out and Availability ✓ ✓ ✓ ✓ In-Memory ✓ ✓ ✓ ✓ Complements 3rd Party DB X ✓ X ✓ Persistence as Extension ✓ X (copy of data in RAM) X (snapshots) ✓ Fast Restarts X X X ✓ Consistency and Transactions X ✓ ✓ ✓ SQL X X ✓ ✓ Collocated Processing X ✓ X ✓ Machine and Deep Learning ✓ X X ✓
  13. 13. 2018 © GridGain Systems Apache Ignite Overview
  14. 14. 2018 © GridGain Systems Memory-centric distributed database, caching, and processing platform In-memory computing platform based Apache Ignite adding enterprise features and support for mission critical deployments
  15. 15. 2018 © GridGain Systems 15 Among Top Apache Projects Top 5 Developer Mailing Lists 1. Beam 2. Ignite 3. Kafka 4. Tomcat 5. James Top 5 User Mailing Lists 1. Flink 2. Lucene 3. Ignite 4. Cassandra 5. Kafka Over 2M downloads per year
  16. 16. 2018 © GridGain Systems In-Memory Computing Benefits In-Memory Speeds 10-1,000x faster than systems built on disk-based databases Massive Scalability Scale out to petabytes of in-memory data Easy to Implement No rip-and-replace of existing databases
  17. 17. 2018 © GridGain Systems Comprehensive Solution • Slides In Between Existing Application and Data Layers • Works With RDBMS, NoSQL and Hadoop Databases • Multi-Language Support Including SQL, Java, .NET, PHP, Node.js, Scala and MapReduce • Deploy On-Premises, In the Cloud, or on Hybrid Environments
  18. 18. 2018 © GridGain Systems eCommerce, Retail & Travel Financial Services Software FinTech Pharma & Healthcare Ignite – Used by Leading Companies Worldwide IoT AdTech Telecom & Mobile Logistics & Transportation
  19. 19. 2018 © GridGain Systems Apache Ignite In-Memory Computing Platform Security&Auditing Monitoring&Management DataSnapshots&Recovery Memory-Centric Storage Scale to 1000s of Nodes & Store TBs of Data Ignite Native Persistence (Flash, SSD, Intel 3D XPoint) Third-Party Persistence Keep Your Own DB (RDBMS, HDFS, NoSQL) SQL Transactions Compute Services MLStreamingKey/Value IoTFinancial Services Pharma & Healthcare E-CommerceTravel & Logistics Telco DataCenterReplication
  20. 20. 2018 © GridGain Systems Distributed In-Memory Data Store In-Memory Data Store GridGain Server Cluster Predictable Memory Consumption Fully Transactional WAL (Write Ahead Log) Instantaneous Restarts Automatic Defragmentation Off-heap Removes Noticeable GC Pauses Stores Superset of Data Distributed Persistent Store In-Memory Data Store Persistent Store Server Node In-Memory Data Store Persistent Store Server Node In-Memory Data Store Persistent Store Server Node
  21. 21. 2018 © GridGain Systems Reference Case Sharing
  22. 22. 2018 © GridGain Systems The ING Group is a Dutch multinational banking and financial services corporation headquartered in Amsterdam. Its primary businesses are retail banking, direct banking, commercial banking, investment banking, asset management, and insurance services. Problem • To deliver new competitive customer services fast • High cost of running on mainframe infrastructure • Transaction consistency over multiple geo-locations GridGain Solution • Powers the core solution for delivering new services Data aggregation across multiple sources • Reduces infrastructure costs Front-End APIs Payments SecuritiesAccounts Credits Clients Multi-datacenter Infrastructure GridGain In-Memory Computing Platform - Next Generation Banking
  23. 23. 2018 © GridGain Systems Wellington - Next Generation, Real-time IBOR A top 20 worldwide asset management firm with over $1 trillion under management • Problem – Current systems no longer scaled to handle the volumes – Didn’t comply with new regulations following financial crisis – Needed to introduce new asset classes faster • GridGain Solution – Investment Book of Record (IBOR), a single real-time version of the truth for positions, exposure, valuations and performance for all customers, teams and trades. – 10x performance gains, linear horizontal scalability – Support for SQL and ACID transactions, and for existing systems and skillsets – Enabled transactions and analytics on a single platform – Collocated computing scales complex calculations, analytics Trading Systems GridGain In-Memory Computing Platform In-Memory Data Grid In-Memory Database Streaming Analytics Continuous Learning Framework Accounting System Other Back Office Portfolio Management Risk Management Regulatory & Compliance Investment Book of Record (IBOR) Oracle RAC
  24. 24. 2018 © GridGain Systems2019 © GridGain Systems Ping An – Accelerate the database performance 24 Ping An Insurance has over 1M sales people generating US$122.4B+ in revenue Front-End APIs SQL TXCompute Service Grid Key / Value Commission Calculation System GridGain In-Memory Computing Platform Distributed In-Memory Data Store Distributed Persistent Store In-Memory Data Store Persistent Store Server Node In-Memory Data Store Persistent Store Server Node In-Memory Data Store Persistent Store Server Node Problems • Calculating sales commissions is a complex matrix math challenge • Key requirements: accuracy and speed • Current platform: Oracle HW+SW for multi-field/range- based queries across 8 or more tables • Goal: achieve 5x improvement in calculation times— without errors GridGain Solution • Reduce cost – Move out from Oracle to GridGain • Improve the delivery performance – the commission calculation change from 8 hours to 1 hour. • Immediate restart from disk (no memory warm-up)
  25. 25. 2018 © GridGain Systems What is Ignite? - Getting Start - - In-memory computing essentials: Part 1 - In-memory computing essentials: Part 2 Download Apache Ignite - Free 30-Day Ultimate, Enterprise or Professional Edition Trial - Next Steps or Any Questions?