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TimeBase is a high-performance time series database developed by Deltix.

Key features include:

  • Embedded data modeling and serialization functionality
  • Streaming system
  • Messaging middleware

TimeBase was initially designed for the very fast aggregation and retrieval of massive volumes of high-frequency financial market data. The same TimeBase technology excels at processing any time-series data, such as financial markets (MBO/ITCH), IoT (MQTT), software metrics and signals, real-time events, logging, and so on.

TimeBase runs standalone or in a cluster, processes millions of messages per second, stores terabytes of data, and offers microsecond latencies.

TimeBase combines multiple solutions into a single package, including:

Key Differentiators

The following features set TimeBase apart from other time series databases:

  • Unified streaming API: Available for both history and live time-series data.
  • High performance: Configure the system to stream data with microsecond-long latencies or to read/write millions of messages per second on each data producer and consumer.
  • Low latency: When streaming live data, TimeBase can feed real-time consumers from memory rather than from the disk, allowing for a significant latency reduction.
  • Complex message structure: TimeBase can store complex message structures that reflect data in your business domain (no need for intermediate DTO objects).
  • Schema-based database: Contains embedded data serialization and a modeling framework allowing for better visibility and data migration. Smooth transition from rapid data prototyping to production solution.
  • Row-based design: Offers better latency and throughput for streaming use cases compared to column-based databases.

To learn more about TimeBase's advantages, please visit the Key Features page.

Typical Tasks

Typical use cases for TimeBase include:

  • Using the data replication framework with multiple out-of-the box integrations or the open multi-language API to create custom integrations.
  • Aggregating massive volumes of heterogeneous time-series data history or real-time data from multiple sources with superior latency and throughput.
  • storing data reliably for heterogeneous time-series data.
  • Rapidly retrieving and streaming of historical and real-time time series data. TimeBase has a sophisticated time series engine, capable of efficiently merging multiple data streams with arbitrary temporal characteristics into a unified query response on-the-fly.
  • Streaming live data provided by readers and writers working simultaneously.
  • Providing a framework for processing and enrichming data, serving as a foundation for building normalization and validation frameworks.
  • Providing statistical models and machine learning with features including:
    • Warm-up mode: Initialization with historical data
    • Parameters estimation
    • Online forecasting
    • Recurring learning: On-the-fly adjustment with up-to-date parameters

To learn more about TimeBase's use cases, visit the Why TimeBase page.