Top 0 Time Series Databases SaaS Companies Under $1M Revenue (September 2026)
As of September 2026, Latka tracks 0 time series databases SaaS companies under $1M in annual revenue.
Every company below sells time series databases software to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.
What Time Series Databases SaaS Companies do
Time series databases (TSDBs) are specialized database systems designed to manage and analyze time-stamped data efficiently. They optimize storage and retrieval to handle the unique characteristics of time series data, which consists of sequences of data points indexed in time order. These databases are particularly useful for tracking and analyzing trends, patterns, and anomalies over time across various domains such as finance, IoT, and network monitoring. Common use cases for time series databases include real-time analytics, performance monitoring, and predictive analytics. Typical features of TSDBs often include high write and query performance with the capability to handle large volumes of rapidly arriving data, compression techniques to reduce storage costs, and functionality for aggregating data points. The primary users of time series databases often include data analysts, IT operations teams, and industries focused on time-sensitive analyses, such as finance and telecommunications.
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Top Time Series Databases SaaS Companies Under $1M Revenue
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Inclusion Criteria
- Must support storing and querying time-stamped data efficiently. - Should provide real-time processing capabilities for continuous data streams. - Must include features for data aggregation and analysis over time intervals. - Should allow for scalability to handle large datasets generated in high-frequency scenarios. - Not just general-purpose databases; must be optimized specifically for time series data use cases.