Time Series Data and OLAP: Why You Should Use InfluxDB for Real-Time Analytics
By
Jason Myers /
Developer
Feb 23, 2024
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Picture a bustling control room at a major aerospace company, where engineers and executives monitor aircraft performance, analyze flight data, and make critical decisions in real-time. In this dynamic environment, the ability to harness the power of real-time analytics becomes paramount. This is where InfluxDB 3.0, the latest version of InfluxData’s time series database, delivers an innovative edge to organizations with time-critical analytics needs.
OLAP and real-time analytics
In industries where every second counts, having the right tools for real-time analytics are table stakes. Online Analytical Processing (OLAP) databases support complex analytical queries on large-scale datasets. Unlike traditional row-oriented databases, OLAP databases take a column-oriented approach, organizing data in individual columns rather than continuously storing rows together. This columnar structure enables fast analytical queries, aggregations, and summarizations across specific columns, making OLAP databases ideal for performing in-depth analysis of vast amounts of data.
OLAP databases provide businesses with the ability to gain valuable insights, make data-driven decisions, and uncover patterns and trends within their data, ultimately driving strategic and operational improvements.
If your organization relies heavily on time series data—to revisit our aerospace company, this may include monitoring flight telemetry, optimizing fuel efficiency, and more— then you want to ensure that your OLAP solution can handle time series data efficiently.
Solving OLAP challenges with time series
InfluxDB 3.0 is a columnar, time series, OLAP database. As such, it addresses many of the needs of OLAP database buyers out of the box.
Performance and Scalability: InfluxDB 3.0’s ability to handle large volumes of time series data and deliver fast query response times is crucial for real-time analytics. It can ingest millions of data points every second and make that data available for immediate query at scale. This enables users to identify patterns and anomalies that impact safety or operational efficiency. With InfluxDB 3.0’s optimized OLAP capabilities, complex analytical queries can be executed swiftly, enabling engineers to make critical decisions promptly.
Data Model and Flexibility: The range of sensors and devices that generate data is broad, meaning organizations need a solution that handles multiple data types and formats. InfluxDB has 300+ integrations to ingest, process, and output data from virtually any machine or device. InfluxDB’s data collection agent, Telegraf, is open source, so users can easily build custom plugins if one doesn’t already exist for their data. InfluxDB 3.0’s flexibility in accommodating different data models allows companies to define hierarchies, dimensions, and measures specific to their needs. This adaptability ensures that users can perform real-time analytics on the most relevant data points, providing valuable insights for optimizing performance and maintenance.
Integration Capabilities: When we redesigned InfluxDB 3.0, we put a premium on interoperability. Built on the Apache Arrow ecosystem (the FDAP stack), InfluxDB enables seamless integration with existing data sources, ETL processes, and BI tools. InfluxDB 3.0’s compatibility with cloud environments and support for popular data formats like Parquet enable effortless integration into the existing technology stack. This empowers companies to leverage their data ecosystem fully, combining real-time analytics with historical data for comprehensive insights.
Security and Support: InfluxDB’s fully-managed solutions (Cloud Serverless and Dedicated) encrypt data at rest and in motion and comply with SOC II type 2 and ISO 27001 specifications. Users have several options for security upgrades and support subscriptions, depending on their needs.
Total Cost of Ownership (TCO): Because of the amount and granularity of time series data, storing all that data can be very expensive. That means that organizations need to choose between keeping high-granularity data and being able to perform accurate historical analysis or keeping costs low. InfluxDB 3.0’s columnar structure, combined with the Parquet file format, delivers significant compression gains, reducing the space needed to store data. Organizations can save 90%+ on data storage costs, which means they can afford to keep critical data longer and use it to generate value.
Database tuning and optimization: InfluxDB 3.0 continues to deliver performance improvements. Users can optimize queries and customize database structures for efficiency and performance.
Get more from your data
InfluxDB 3.0’s real-time OLAP capabilities empower organizations across industries to harness the power of real-time analytics like never before. InfluxDB 3.0 revolutionizes how users analyze data, enabling prompt decision-making, optimizing performance, and ensuring cost-effective operations. When monitoring is a mission-critical process, an OLAP database like InfluxDB provides the features and capabilities that businesses need to meet their goals, improve performance, and boost their bottom line.
