GridGain In- Memory Data Fabric: UlCmate Speed and Scale for TransacCons and AnalyCcs
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1 GridGain In- Memory Data Fabric: UlCmate Speed and Scale for TransacCons and AnalyCcs DMITRIY SETRAKYAN Founder & EVP #gridgain
2 Agenda EvoluCon of In- Memory CompuCng GridGain In- Memory Data Fabric Distributed Cluster & Compute Coding Example Distributed Data Grid Coding Examples Distributed Streaming & CEP Plug- n- Play Hadoop Accelerator
3 What is In- Memory CompuFng High Performance & Low Latencies Faster than Disk and Flash Cost EffecCve Distributed or Not Caching, Streaming, ComputaCons Data Querying SQL or Unstructured VolaCle and Persistent OLAP and OLTP Use Cases
4 EvoluFon of In- Memory CompuFng Streaming Data Grid Clustering & Compute Grid Database IM opcons Hadoop accelerators Streaming BI accelerators In- Memory Data Grids IMDBs Distributed Caching Caching 2014 GridGain Systems, Inc. Hadoop Acceleration
5 ExisFng Market is Fragmented Company Product Proprietary/ Open Source CharacterizaFon Oracle In-Memory Option for Oracle Database Proprietary Cost Option Oracle Times Ten Proprietary Point Solution IMDB Oracle Coherence Proprietary Point Solution IMDG SAP Hana Proprietary Point Solution - IMDB Microsoft SQL Server 2014 Proprietary Feature Upgrade DataBricks Apache Spark Open Source Point Solution - Hadoop VoltDB VoltDB Open Source Point Solution IMDB Aerospike Aerospike Open Source Point Solution NoSQL DB IBM DB2 with BLU Acceleration Proprietary Feature Upgrade Software AG Terracotta Open Source Point Solution - IMDG Hazelcast Hazelcast Open Source Point Solution - IMDG
6 GridGain In- Memory Data Fabric: Strategic Approach to IMC Supports all Apps Streaming Data Grid Clustering & Compute Grid Hadoop Acceleration Open Source Apache 2.0 Simple Java APIs 1 JAR Dependency High Performance & Scale Automatic Fault Tolerance Management/Monitoring Runs on Commodity Hardware Supports existing & new data sources No need to rip & replace
7 Direct API for MapReduce Direct API for Fork/Join Zero Deployment Cron- like Task Scheduling State Checkpoints Early and Late Load Balancing AutomaCc Failover Full Cluster Management Pluggable SPI Design Clustering & Compute
8 AutomaFc Cluster Discovery
9 Closure ExecuFon
10 Closure ExecuFon
11 In- Memory Caching and Data Grid Distributed In- Memory Key- Value Store Replicated and ParCConed TBs of data, of any type On- Heap and Off- Heap Storage Backup Replicas / AutomaCc Failover Distributed ACID TransacCons SQL queries and JDBC driver CollocaCon of Compute and Data
12 Cache OperaFons
13 Cache TransacFon
14 Distributed Java Data Structures Distributed Map (cache) Distributed Set Distributed Queue CountDownLatch AtomicLong AtomicSequence AtomicReference Distributed ExecutorService
15 Client- Server vs Affinity ColocaFon Client- Server Affinity ColocaCon
16 In- Memory Streaming & CEP Streaming Data Never Ends Branching Pipelines CEP Sliding Windows Pluggable RouCng Real Time Analysis At Least Once Guarantee
17 Plug- n- Play Hadoop Accelerator Up to 100x AcceleraCon In- Memory NaCve MapReduce In- Process Data ColocaCon Eager Push Scheduling GGFS In- Memory File System Pure In- Memory Write- Through to HDFS Read- Through from HDFS Sync and Async Persistence
18 In- Memory NaFve MapReduce In- Memory NaCve MapReduce Zero Code Change Use exiscng MR code Use exiscng Hive queries No Name Node No Network Noise In- Process Data ColocaCon Eager Push Scheduling
19 DevOps Management and Monitoring
20 THANK YOU
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