Introduction to DataStax Enterprise Graph Database
Download as PPTX, PDF2 likes16,933 views
The document introduces DataStax Enterprise Graph, focusing on its relevance for managing complex relationships in cloud applications. It emphasizes the advantages of graph databases for analyzing dynamic connections between data, supports property graph models, and outlines key features for data management and analysis. Use cases highlighted include customer 360 views, asset management, and security/fraud detection, showcasing the database's ability to solve real-world problems efficiently.
Introduction to DataStax Enterprise Graph Database
- 2. Agenda ā 3 Goals 1. Why a Graph Database 2. Why DSE Graph for Cloud Applications 3. Key Features of DSE Graph to Support Cloud Applications Jonathan Lacefield ā Sr. Product Manager ā DSE Graph and Multi Model [email protected] Ā©2016 DataStax Confidential. Do not distribute without consent.
- 3. Problem(s) That Drive a Graph Database 1. Databases were built to store Things, not Relationships! ā Databases were optimized to extract well defined, mostly static, related things - Join + Index ā Hacks were created to handle almost well defined, mostly static, related things - Dynamic Queries 2. Todayās world is driven by Related Things that are ever changing, constantly expanding, and are doing so rapidly. Ā©2016 DataStax Confidential. Do not distribute without consent. The time for the Graph Database has come!
- 4. Ā©2015 DataStax High Level Used to manage highly connected or complex relationships User Level Used to support traversal and analytic queries against a data model that uses vertices, edges and properties to represent and store data Technical Level Uses specialized index structures, data partitioning techniques, and query optimizers to efficiently traverse large graphs What is a Graph Database?
- 5. Ā©2016 DataStax Confidential. Do not distribute without consent. ā¢ A database for storing, managing and querying highly connected and complex relationships. ā¢ A graph databaseās architecture makes it particularly well suited for unlocking the value in the dataās relationships and finding commonalities and anomalies in large data volumes. What is a Graph Database?
- 6. Problem(s) That Drive the DSE Graph Database The first versions of Graph Databases have been focused on ā¦ 1. storing and analyzing related things 2. offline analysis of graph data Ā©2016 DataStax Confidential. Do not distribute without consent. The DSE Graph Database is the best choice for Cloud Application Graph Problems
- 7. ā¢ A scale-out graph database purposely built for cloud applications that need to act on complex and highly connected relationships. ā¢ Supports a property graph model natively inside the DataStax product, engineered specifically for DataStax Enterprise (Cassandra, Search, Analytics). ā¢ Store & find relationships in data fast and easy in large graphs. ā¢ Part of DSEās multi-model platform. What is DataStax Enterprise (DSE) Graph? Ā©2016 DataStax Confidential. Do not distribute without consent.
- 8. Use Cases Use Case Domain Problem DSE Graph Approach Customer 360 How can I smartly understand, navigate, analyze, and act on my Customer data and their relationships that are consolidated across many different systems to get a holistic view of my customer? Use relationships to connect disparate data sources and provide an always up to date Customer profile to users. Asset Management How can I easily perform analysis on numerous relationships that form among data elements and tend to be of much greater interest when examined collectively than reviewed in isolation? A graph is also a good model for managing network assets (with their properties or configurations) and how they relate to each other over time. Security/Fraud How can I quickly determine which entity, transaction or interaction is fraudulent, poses a security risk, or is a compliance concern? In a complex and highly interrelated network of users, entities, transactions, events, and interactions, a graph database can quickly find the bad needle in a haystack of relationships and events that involve countless financial interactions. Ā©2016 DataStax Confidential. Do not distribute without consent.
- 9. Cloud Application Needs Need DSE Graph Feature Store and Access Data Quickly Graph Data Model + Gremlin Flexible, Fast Application Builds DSE Graph + DSE Studio & DSE Drivers Analyze Information Graph Analytics with DSE Analytics Search and Find Quickly Graph Search with DSE Search Ingest and Export Data DSE Graph Loader Secure Information DSE Security Manage and Monitor Opscenter Availability, Scale, Operational Ease, Performanceā¦ DataStax Enterprise Ā© 2016 DataStax, All Rights Reserved. 9
- 10. Property Graph Concepts Ā©2015 DataStax ļ ļ ļ ļ ļ ļ ļ ļ DataStax DataBricks Spark DSE CassandraJonathan Ellis Robin Schumacher Billy Bosworth worksFor title: VP Product develops uses uses reportsTo worksFor title: CTO worksFor title: CEO Property Edge Vertex
- 11. Ā© DataStax, All Rights Reserved. 11 g.V().has("name","gremlin"). repeat(in("manages")).until(has("title","ceo")). path().by("name") >> The management chain from Gremlin to the CEO tinkerpop.apache.org Gremlin
- 12. ā¢ Web-based developer solution which helps developers visually explore, query, and trouble-shoot DSE Graph in one intuitive UI. ā¢ Auto-completion, result set visualization, execution management, and much more. Developer support with DataStax Studio
- 13. Ā©2016 DataStax ā¢ DSE Graph has seamless support for DSE Analytics powered by Apache Spark. ā¢ No need to learn Spark ā Gremlin language used both for OLTP and OLAP. ā¢ Analytics workloads can be separated from OLTP workloads. ā¢ Automatic workload management and replication keep data in sync. Graph Analytics with DSE Analytics
- 14. Ā©2016 DataStax ā¢ DSE Graph has seamless support for DSE Search powered by Apache Solr. ā¢ Simple, schema-driven index management. ā¢ DSE Graphās query optimizer automatically uses Solr behind the scenes. ā¢ Search workloads can be separated from OLTP workloads. Graph Search with DSE Search
- 15. ā¢ Simplifies loading large amounts of enterprise data from various sources into DSE Graph efficiently and robustly. ā¢ Inspects incoming data for schema compliance. ā¢ Uses declarative data mappings and custom transformations to handle diverse types of data. Data Loading Support with DSE Graph Loader Graph Loader ļ ļļ Data Mappings Batch Loading Stream Ingestion RDBMSJSON DSE Graph
- 16. Ā©2016 DataStax ā¢ DSE Graph leverages the investments in Security contained in DataStax Enterprise. ā¢ Object Permissions - Limit access to keyspaces and tables used by DSE Graph ā¢ Transparent Data Encryption ā Encrypt data at rest ā¢ Client-to-Node Encryption ā SSL support for communicating with a Graph cluster ā¢ Secure Authentication ā Kerberose, Password, or LDAP Authentication options DSE Graph Security
- 17. ā¢ Web-based operations solution which can launch, manage, monitor and trouble- shoot DSE clusters and deployments. ā¢ Launch wizard, failure alerts, monitoring dashboards, and much more. Operational support with DataStax OpsCenter
- 18. A Complete Integrated Solution for Graph Ā© 2016 DataStax, All Rights Reserved. 18 Server Visual Management/Monitoring Visual Development Integrated Drivers (CQL, Gremlin, etc.) Java Python C++ Moreā¦
- 19. ā¢ A scale-out graph database purposely built for cloud applications that need to act on complex and highly connected relationships. ā¢ DSE Graph inherits all of the native power of Cassandra as well as the enterprise functionality of DSE, making it the first and best choice for todayās enterprise systems that require graph support. Ā©2016 DataStax Confidential. Do not distribute without consent. Conclusions
Editor's Notes
- #2: 1