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Top 4 Real-time Analytic Database Software SaaS Companies in May 2026

As of May 2026, there are 4 SaaS companies in Real-time Analytic Database Software. They have combined revenues of $229.2M and employ 732 people. They have raised $558.6M and serve 8.5K customers combined.

Real-time analytic database software enables organizations to analyze and process data as it is generated, providing instant insights and facilitating immediate decision-making. This software is particularly useful in scenarios that require the continuous ingestion of streaming data, often seen in applications such as customer behavior tracking, smart device responses, and operational performance monitoring. Typical features of real-time analytic databases include low-latency query capabilities, high throughput for concurrent queries, and support for complex event processing. Common user personas include data analysts, business intelligence professionals, and IT operations teams, who leverage these tools to drive analytics processes within industries such as finance, e-commerce, and telecommunications, where timely access to data is critical for strategic advantage.

Companies
4
Revenue
$229.2M
Funding
$558.6M
Employees
732

Filters

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Filters
Revenue
All<$1M$1M-$5M$5M-$10M$10M-$100M$100M+
Funding (Locked)Growth (Locked)Team-Size (Locked)

Top Real-time Analytic Database Software Companies

Showing 10 of 1 companies ranked by annual revenue.

1
ClickHouse

Redwood City, California, United States

ClickHouse is an open-source, column-oriented OLAP database management system that allows users to generate analytical reports using SQL queries in real-time. Its technology works 100-1000x faster than traditional database management systems, and processes hundreds of millions to over a billion rows and tens of gigabytes of data per server per second. With a widespread user base around the globe, the technology has received praise for its reliability, ease of use, and fault tolerance. Learn more at clickhouse.com.

Revenue
$15M
Customers
-
Year founded
2021
Funding
-
Team size
197
Growth
-

Inclusion Criteria

- The software must support real-time data ingestion and processing. - It should provide low-latency query response for immediate insights. - It must be capable of handling high volumes of concurrent queries. - The product should allow for complex event processing and analytics. - It should offer integration capabilities with various data sources. - Not just focused on historical data analysis; must also provide real-time analytical functionalities.