Oracle TimesTen

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#Databases #Relational Databases #NoSQL Databases #Network & Admin

JanusGraph

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#Graph Databases #Databases #NoSQL Databases #Big Data

Oracle TimesTen features and specs

• High Performance
  Oracle TimesTen is an in-memory database providing extremely fast data access and transaction processing, which is beneficial for applications that require real-time performance.
• Low Latency
  Since the database is stored in memory, data retrieval and manipulation are very quick, reducing latency significantly compared to disk-based databases.
• Scalability
  TimesTen can be easily scaled to handle large volumes of data and transaction loads, supporting hybrid configurations with Oracle Database to extend scalability and reliability.
• SQL Compatibility
  It supports SQL and PL/SQL, making it easier for developers experienced with Oracle databases to use TimesTen without a steep learning curve.
• High Availability
  TimesTen offers features like replication and failover for high availability which is crucial for mission-critical applications.
• Integration with Oracle Ecosystem
  TimesTen integrates well with other tools and products in the Oracle ecosystem, allowing for seamless operations across different Oracle platforms.

Possible disadvantages of Oracle TimesTen

• Cost
  Oracle TimesTen can be expensive compared to some of its open-source alternatives, making it less attractive for smaller businesses or projects with limited budgets.
• Hardware Dependency
  Being an in-memory database, it requires machines with large RAM capacities to store substantial datasets, which can be a limiting factor.
• Complexity
  Setting up and managing TimesTen can be complex, especially when trying to optimize for performance and ensure data consistency across systems.
• Limited Community Support
  Unlike more popular database systems, the community support for TimesTen is limited, which means troubleshooting and problem-solving might not be as straightforward.
• Data Volatility
  Since TimesTen stores data in memory, there’s a risk of data loss in the event of power failures, despite having persistence features to mitigate this risk.

JanusGraph features and specs

• Scalability
  JanusGraph is designed to support large-scale graph data processing, allowing it to handle huge graphs distributed across multiple machines effectively.
• Compatibility
  It is compatible with various storage backends (like HBase, Apache Cassandra, and Google Bigtable) and indexing backends (such as Elasticsearch and Solr), providing flexibility in integration.
• APIs and Queries
  JanusGraph supports the TinkerPop stack, enabling developers to use powerful graph traversal language Gremlin for query operations.
• Open Source
  Being open-source, JanusGraph benefits from community contributions and offers transparency and extensibility to users.
• Transaction Support
  It provides ACID transactions, ensuring reliability and consistency in graph operations.

Possible disadvantages of JanusGraph

• Complexity
  The configuration and optimization of JanusGraph can be complex due to its support for multiple backends and the various configurations required for different setups.
• Performance Variability
  Performance can vary significantly depending on the chosen backend datastore and its configuration, requiring careful consideration and tuning.
• Operational Overhead
  Managing the infrastructure, especially when using distributed storage solutions, can introduce significant operational overhead.
• Community and Support
  While it is open source, the community is not as vast or active as some other database technologies, which may limit available support and resources.
• Resource Intensity
  Running JanusGraph with large datasets and multiple distributed nodes can require substantial resources, both in terms of hardware and maintenance.

My demo of Oracle TimesTen in memory DB with Free Developer Day tools with a VirtualBox VM appliance

Ted Wilmes on the state of JanusGraph 2018

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