{"id":11485,"date":"2023-02-20T16:58:39","date_gmt":"2023-02-21T00:58:39","guid":{"rendered":"https:\/\/tdengine.com\/?p=11485"},"modified":"2025-11-03T08:16:37","modified_gmt":"2025-11-03T16:16:37","slug":"devops-performance-comparison-influxdb-and-timescaledb-vs-tdengine","status":"publish","type":"post","link":"https:\/\/tdengine.com\/devops-performance-comparison-influxdb-and-timescaledb-vs-tdengine\/","title":{"rendered":"DevOps Performance Comparison: InfluxDB and TimescaleDB vs. TDengine"},"content":{"rendered":"\n
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An in-depth look at the performance of key time-series databases<\/em><\/p>\n\n\n\n

For a quick overview, see our infographic<\/a> or watch a video<\/a><\/em><\/p>\n<\/blockquote>\n\n\n\n

The sheer volume and complex nature of time-series data has given rise to the purpose-built time series database<\/a> (TSDB). While performance is crucial for all databases, the scale and complexity of time-series data makes performance, precision, and scalability especially important.<\/p>\n\n\n\n

The performance of your TSDB doesn\u2019t just impact your ability to ingest, store, and analyze large amounts of data; it directly affects your total cost of ownership<\/a> (TCO). Better ingestion rates, query response times and compression ratios mean your system consumes fewer resources to process the same amount of data. To demonstrate TDengine’s robust performance<\/a>, we evaluated the platform against two key players in this space: InfluxDB and TimescaleDB.<\/p>\n\n\n\n

The findings clearly show that TDengine offers significant advantages over both InfluxDB and TimescaleDB<\/em> in terms of data ingestion, compression, and query performance. In addition, TDengine uses fewer server-side CPU resources than either competing time series DB to process identical datasets.<\/p>\n\n\n\n

Objective Evaluation via the Time Series Benchmark Suite<\/h2>\n\n\n\n

To ensure an even playing field, we used the open source Time Series Benchmark Suite (TSBS) framework and ran the tests on identical systems in AWS. TSBS is designed for objective database evaluations and generates datasets for a range of recommended ingestion and query scenarios. TSBS is used by other database providers, including VictoriaMetrics and Timescale, to perform evaluations similar to the one described here.<\/p>\n\n\n\n

TSBS is an open and independent framework, meaning the test procedures and datasets generated aren’t designed to benefit any database platform, and allows anyone to conduct an objective evaluation.<\/p>\n\n\n\n

This evaluation applied the TSBS DevOps dataset, which includes small and large-scale scenarios, each with ten metrics, ten tags, and a microsecond-precision timestamp. For detailed information, see the official TSBS repository in GitHub<\/a>.<\/p>\n\n\n\n

Performance Comparison<\/h2>\n\n\n\n

Ingestion Performance<\/h3>\n\n\n\n

Time series databases need to ingest massive amounts of data, and TDengine achieves the fastest ingestion speeds across all TSBS scenarios<\/em>, ranging from 1.5 to 10.6 times the speed of the other products.<\/p>\n\n\n\n

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TDengine ingests data significantly faster than TimescaleDB or InfluxDB<\/figcaption>\n<\/figure>\n\n\n\n

Resource Consumption<\/h3>\n\n\n\n

In addition, TDengine uses less processing power than InfluxDB or TimescaleDB<\/em> to ingest the datasets. At its peak, InfluxDB’s CPU usage exceeds 90% during the ingestion process, while TDengine remains under 15%. Although TimescaleDB used a similar amount of CPU resources to TDengine, it spent far more time to compress and order the data after writing it to the database.<\/p>\n\n\n\n

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TDengine has low CPU usage, while InfluxDB demands significant processing resources<\/figcaption>\n<\/figure>\n\n\n\n

Query Performance<\/h3>\n\n\n\n

As performance can differ based on a number of factors, the TSBS framework covers a wide range of query types. TDengine provided the fastest query response across all scenarios<\/em>, confirming that organizations dependent on real-time analytics are best served with this purpose-built platform.<\/p>\n\n\n\n

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For simpler queries, TDengine’s response time was 1.9 to 12.1 times faster than InfluxDB and TimescaleDB<\/figcaption>\n<\/figure>\n\n\n\n

More complex queries allowed TDengine to show off its processing power, reaching 24.3 times the performance of TimescaleDB and 34.3 times the performance of InfluxDB in the most challenging scenario: double-groupby-all<\/em>. This demonstrates that TDengine is best prepared to handle the most performance-intensive queries without slowing down. <\/p>\n\n\n\n

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TDengine processes queries significantly faster than InfluxDB or TimescaleDB, especially for complex scenarios<\/figcaption>\n<\/figure>\n\n\n\n

The performance of TDengine in the other TSBS query categories was as follows:<\/p>\n\n\n\n