Apache Ignite TM (Incubating) - In- Memory Data Fabric Fast Data Meets Open Source
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1 Apache Ignite TM (Incubating) - In- Memory Data Fabric Fast Data Meets Open Source DMITRIY SETRAKYAN Founder,
2 Agenda About In- Memory Computing Apache Ignite (tm) In- Memory Data Fabric Advanced Clustering Data Grid Compute Grid Service Grid Ignite For Analytics Streaming & CEP Share State Across Spark Jobs In- Memory MapReduce Interactive SQL DevOps: Yarn and Mesos Q & A
3 Apache Ignite TM In- Memory Data Fabric: Strategic Approach to IMC Supports Applications of various types and languages 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
4 In- Memory Data Fabric: More Than Data Grid
5 Apache Ignite: Better Cloud Support Automatic Discovery Simple Configuration AWS/EC2/S3 Google Compute Engine (NEW) Other Clouds with JClouds (NEW) Docker Support Automatically Build and Deploy
6 Data Grid: JCache (JSR 107) JCache (JSR 107) Basic Cache Operations ConcurrentMap APIs Collocated Processing (EntryProcessor) Events and Metrics Pluggable Persistence Ignite Data Grid ACID Transactions SQL Queries (ANSI 99) In- Memory Indexes Automatic RDBMS Integration
7 Data Grid: Partitioned Cache
8 Data Grid: Replicated Cache
9 Data Grid: Off- Heap Memory Unlimited Vertical Scale Avoid Java Garbage Collection Pauses Small On- Heap Footprint Large Off- Heap Footprint Off- Heap Indexes Full RAM Utilization Simple Configuration
10 Data Grid: Ad- Hoc SQL (ANSI 99) ANSI- 99 SQL Always Consistent Fault Tolerant In- Memory Indexes (On- Heap and Off- Heap) Automatic Group By, Aggregations, Sorting Cross- Cache Joins, Unions, etc. Ad- Hoc SQL Support
11 SQL Cross- Cache JOIN Example
12 SQL Cross- Cache GROUP BY Example
13 In- Memory Compute Grid Direct API for MapReduce Direct API for ForkJoin Zero Deployment Cron- like Task Scheduling State Checkpoints Load Balancing Automatic Failover Full Cluster Management Pluggable SPI Design
14 In- Memory Streaming and CEP Streaming Data Never Ends Branching Pipelines Pluggable Routing Sliding Windows for CEP/Continuous Query SQL Queries (ANSI 99) Query Across Sliding Windows Real Time Analysis
15 In- Memory Service Grid Singletons on the Cluster Cluster Singleton Node Singleton Key Singleton Distribute any Data Structure Available Anywhere on the Grid Access Anywhere via Proxies Guaranteed Availability Auto Redeployment in Case of Failures
16 Apache Ignite for BI and Analytics
17 DevOps: Integration with Yarn and Mesos Automatic Resource Management Easy Data Center Installation Easy Data Center Configuration On- Demand Elasticity
18 Share RDDs Across Spark Jobs IgniteRDD Share RDD across jobs on the host Share RDD across jobs in the application Share RDD globally Faster SQL In- Memory Indexes SQL on top of Shared RDD
19 Ignite In- Memory File System Ignite In- Memory File System (IGFS) Hadoop- compliant Easy to Install On- Heap and Off- Heap Caching Layer for HDFS Write- through and Read- through HDFS Performance Boost
20 Ignite In- Memory Map Reduce In- Memory Native Performance Zero Code Change Use existing MR code Use existing Hive queries No Name Node No Network Noise In- Process Data Colocation Eager Push Scheduling
21 Interactive SQL with Apache Zeppelin
22 GridGain Enterprise & Apache Ignite Comparison Chart Features Apache Ignite Enterprise Edition In-Memory Data Grid In-Memory Compute Grid CHECK Real-Time Streaming & CEP Hadoop Acceleration Management & Monitoring GUI Portable Objects.Net and C++ APIs Enterprise-grade Security Network Segmentation Protection Local Restartable Store Rolling Production Updates Datacenter Replication 9x5 and 24x7 Support Long Term Support & Patches GridGain Enterprise Subscriptions include the following during the term of the subscription: > Right to use GridGain Enterprise Edition > Bug fixes, patches, updates and upgrades > 9x5 or 24x7 Support > Ability to procure Training and Consulting Services from GridGain > Confidence and protection, not provided under Open Source licensing, that only a commercial vendor can provide, such as indemnification
23 ANY QUESTIONS? Thank you for joining us. Follow the
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