1. Introduction
  2. Using TimesTen
  3. Uses for TimesTen Scaleout

Uses for TimesTen Scaleout

TimesTen Scaleout is used for multiple-instance environments and distributed databases. TimesTen Scaleout provides fast access, fault tolerance, and high availability for in-memory data.

With TimesTen Scaleout, you can:

  • Create a grid that is a set of interconnected instances installed on one or more hosts.

  • Maintain one or more copies of your data. Your choice to maintain more than one copy protects you from data loss in the event of a single failure.

  • Distribute the data of each database across the instances in the grid in a highly available manner using a shared-nothing architecture.

  • Connect applications to your database with full access to all the data, no matter what the distribution of the data is across the database.

  • Add or remove instances from your grid to:

    • Expand or shrink the storage capacity of your database as necessary.

    • Expand or shrink the computing resources of your database to meet the performance requirements of your applications.

See Overview of TimesTen Scaleout in the Oracle TimesTen In-Memory Database Scaleout User's Guide.

TimesTen Scaleout Application Scenario

A typical use case scenario for TimesTen Scaleout is an Internet-of-Things (IoT) application.

TimesTen Scaleout is used to:

  • Capture semi real-time data (sensor readings, geolocation data, telemetry, and so on) from a vast array of connected devices.

  • Aggregate and analyze data in real-time (for alerting purposes) before offloading data to other systems for further reporting and analysis.

The Internet is pervasive as more and more devices are connected (such as smart homes, smart phones, tablets, cars, domestic appliances, utility meters, exercise devices, GPS trackers, RFID tags, and so on). Many services need to efficiently capture and process huge volumes of data generated in a real-time by these devices.

Figure 2-1 Using TimesTen Scaleout for an Internet-of-Things Application

Description of Figure 2-1 follows
Description of "Figure 2-1 Using TimesTen Scaleout for an Internet-of-Things Application"

A TimesTen Scaleout application example illustrates how a vendor of smart home technology uses TimesTen Scaleout to capture sensor data (temperature, humidity, CO2 levels, device events). Once captured, the data is aggregated and analyzed in order to generate real-time alerts for anomalous conditions and then the aggregated data is offloaded to other systems for archival storage, in depth analysis, and so on. Once offloaded, the data is purged from the database.

  • Capture: Sensor data collected from the smart home devices is sent over the Internet to the data collection applications running in the same vicinity as the database. These applications insert and update data in the database based on the received data.

  • Aggregate and analyze: Real-time aggregation and alerting applications perform initial processing on the data as it arrives. If the application detects any important events, then the application sends alerts to the smart home devices, user's smartphone applications, and so on.

Offload and purge applications move historical aggregated data that is no longer needed online to storage, for long term storage and analysis. Once moved into storage, the aggregated data and underlying raw data is purged from the database.

TimesTen Scaleout is ideal for this type of application:

  • High throughput and low latency enables TimesTen Scaleout to cope with a heavy read-write workload.

  • Fault tolerant architecture enables TimesTen Scaleout to deliver continuous uptime even in the event of hardware or software failures.

  • Elastic scalability features enable the storage and processing capacity of the database to dynamically increase while remaining online.

  • Support for a broad range of industry standard languages and APIs makes building different application components easy for developers.