Times Adder Pricing: Plans, Free Tier, and Cost Examples (2026)

Pricing overview

Times Adder offers a tiered pricing structure primarily based on the volume of API requests per month. This model is designed to accommodate various usage levels, from individual developers experimenting with time series data to enterprises requiring extensive real-time data processing. The pricing includes a free developer tier, allowing users to test the platform's capabilities before committing to a paid plan. As usage scales, the cost increases proportionally with the number of API calls made, ensuring users pay for the resources they consume.

The core components driving the pricing are API requests to the Time Series Aggregation API, Anomaly Detection API, and Forecasting API. These services are central to Times Adder's offerings for analyzing and predicting trends in time-series datasets. The pricing structure is detailed on the Times Adder official pricing page, which provides current rates and plan specifics.

Plans and tiers

Times Adder provides several plans, each tailored to different usage requirements and offering varying request limits and features. The plans are structured to provide scalability as an application's demand for time series analysis grows.

Each paid plan includes access to all core API functionalities, with higher tiers often benefiting from enhanced support, higher rate limits, and potentially lower per-request costs at scale. For instance, the Professional Plan offers a substantial increase in request capacity, making it suitable for applications that require frequent data aggregation and anomaly detection across numerous data streams.

Free tier and limits

Times Adder offers a Developer Plan as its free tier. This plan is designed to allow developers to explore the platform's capabilities without an initial financial commitment. It includes access to the Time Series Aggregation API, Anomaly Detection API, and Forecasting API, enabling users to build and test applications that require time series analysis functionalities.

• Monthly Request Limit: 5,000 API requests.
• Included APIs: Full access to core Time Series Aggregation, Anomaly Detection, and Forecasting APIs.
• Support: Community support forums.

The Developer Plan is suitable for prototyping, educational projects, or small-scale personal applications. Users can leverage this free tier to integrate Times Adder's Python, JavaScript, or Go SDKs and develop proof-of-concept applications. Once usage exceeds 5,000 requests per month, users must upgrade to a paid plan to continue service without interruption. The limits are reset monthly, providing a consistent testing environment for ongoing development.

Real-world cost examples

To illustrate the pricing structure, consider several common usage scenarios for Times Adder:

Scenario 1: Small IoT Sensor Monitoring

An application monitors data from 50 IoT sensors, each sending data every 10 minutes. The application uses the Time Series Aggregation API to consolidate this data hourly. This results in approximately:

• 50 sensors * 6 requests/hour * 24 hours/day * 30 days/month = 216,000 requests/month.

This usage would exceed the Basic Plan's 50,000 requests. It would fall within the Standard Plan's 250,000 requests/month limit. The estimated cost would be $99 per month for the Standard Plan. If the application also performs anomaly detection on each hourly aggregation, this could double the request count, potentially pushing it towards the Professional Plan.

Scenario 2: Financial Data Analysis for a Startup

A financial tech startup uses Times Adder's Forecasting API to predict stock movements for 100 different assets daily. Each prediction involves 3 API calls (data retrieval, model training, prediction call). This translates to:

• 100 assets * 3 API calls/asset * 22 trading days/month = 6,600 requests/month.

This usage fits within the Basic Plan's 50,000 requests/month limit. The estimated cost would be $29 per month. If the startup expands to analyze thousands of assets or performs real-time intraday predictions, the request volume would quickly necessitate an upgrade to higher tiers.

Scenario 3: Predictive Maintenance for Industrial Equipment

An industrial company monitors 20 critical machines, performing anomaly detection every 30 minutes on each machine's operational data. This involves:

• 20 machines * 2 requests/hour (for data aggregation and anomaly check) * 24 hours/day * 30 days/month = 28,800 requests/month.

This usage remains within the Basic Plan's 50,000 requests/month limit. The estimated cost would be $29 per month. If the monitoring frequency increases or the number of machines grows, the cost would scale accordingly. For example, monitoring 100 machines at the same frequency would require 144,000 requests/month, placing it in the Standard Plan.

How the pricing compares

Times Adder's pricing model, based on API request volume, is a common approach among API-centric services. When comparing it to alternatives like InfluxData, Grafana, or Datadog, several factors come into play beyond just the raw price per request.

• InfluxData: InfluxData offers both open-source and cloud-based solutions. Their cloud pricing often considers data ingestion, storage, and queries, rather than just API requests. For instance, InfluxDB Cloud pricing is typically based on data writes per second and data storage, which can be more complex to estimate for some users compared to a straightforward request count.
• Grafana: Grafana is primarily an open-source visualization tool, and its core product is free. However, Grafana Cloud pricing bundles monitoring, logging, and tracing, often charging per active series, log data ingested, and trace spans. This holistic approach can be more expensive for users who only require specific time series analysis APIs.
• Datadog: Datadog offers a comprehensive monitoring and analytics platform. Its pricing is granular, with separate charges for infrastructure monitoring (per host), APM (per host/GB ingested), logs (per GB ingested), and various other services. A user needing only time series analysis from Datadog might find themselves paying for features they don't fully utilize, as detailed on Datadog's pricing page.

Times Adder's focus on a clear request-based model for its specialized time series APIs can offer a more predictable cost for developers and businesses specifically focused on aggregation, anomaly detection, and forecasting, without the overhead of broader monitoring or data storage costs that characterize some competitors. This can be particularly advantageous for applications that are data-intensive but do not require extensive infrastructure monitoring or log management from the same vendor.

The simplicity of a request-based model, as described by the Google Cloud pricing models documentation, often appeals to developers who need to forecast API costs directly related to their application's activity. While alternatives may offer broader platforms, Times Adder's targeted approach with transparent request-based pricing provides a distinct option for specialized time series analysis needs.