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Persistence and Datastore

Persistence and Datastore. Discussion. Discussion Outline. Generalize Datastore API to Support: Existing Datastore (Data Tree) Alternative Datastores Application Aware Datastore (Hash, Alternative Trees, etc ) Database-Backed (Relational, NoSQL) Persisting Non-Modeled Data

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Persistence and Datastore

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  1. Persistence and Datastore Discussion

  2. Discussion Outline • Generalize Datastore API to Support: • Existing Datastore (Data Tree) • Alternative Datastores • Application Aware Datastore (Hash, Alternative Trees, etc) • Database-Backed (Relational, NoSQL) • Persisting Non-Modeled Data • Potential Persistence Implementation With Hibernate (ORM/OGM)

  3. Why Support Databases? • Core Projects Need It (AAA) Outside of MD-SAL • Potentially Large Datasets to Persist • Long-Term Storage and Querying • Alternative Datastores • Not All Data Should Be Both In Memory and Persisted in Data Trees • e.g. Persist Alert/Audit Logs • Additional Datastore Benefits from DBs and Frameworks (Caching, Distribution, Query Language, Indexing, etc.)

  4. Open Questions • Should All APPs Have to Model (Yang) Data to Persist? • What Is a Common API for All ODL Datastores? • Performance? (In and Outside of MD-SAL)

  5. Hibernate (ORM/OGM) • Mapping Library (Object  Relational/NoSQL DBs) • Pluggable Databases (JDBC) • Data Validation (Built-In & Custom) • Query Support (HQL, SQL, Criteria Query) • Transactions (JTA) • Session (Batching) • Monitoring / Logging / Statistics • Optional Features: • Caching (L1/L2 – Query Level) • Search (Lucene)

  6. Hibernate (ORM/OGM)

  7. Q&A

  8. Resources • Contacts: • Mark Mozolewski (mbm@hp.com)

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