StarRocks: A Open Source OLAP Database for Fintech

StarRocks OLAP database for Fintech

StarRocks is a next-generation, blazing-fast massively parallel processing (MPP) database designed to make real-time analytics easy for enterprises. It is built to power sub-second queries at scale, making it ideal for fintech applications such as fraud detection, risk management, and real-time trading.

Here are some of the ways that StarRocks can benefit fintech companies:

• Real-time analytics: StarRocks can process data in real time, allowing fintech companies to make decisions based on the latest information. This is critical for applications such as fraud detection and risk management, where even a small delay can have significant consequences.
• Scalability: StarRocks is highly scalable, allowing fintech companies to handle large volumes of data without sacrificing performance. This is important for fintech companies that need to process large amounts of transaction data, market data, and other types of data.
• Flexibility: StarRocks is a flexible database that can be used for a variety of workloads, including real-time analytics, batch processing, and ad-hoc queries. This makes it a good choice for fintech companies that need to use different types of analytics to support their business.

StarRocks is an open source query engine that that delivers data warehouse performance on the data lake. In our internal testing StarRocks Offers 2.2x Performance over ClickHouse and 8.9x Performance over Apache Druid® in Wide-table Scenarios Out of the Box using product native table format and 5.54x Query Performance over Trino in Multi-table Scenarios using Apache Iceberg table format with Parquet files. Read more at https://www.starrocks.io/blog/benchmark-test

Query data on top of the lake, support performant JOINS at scale, support 1000s of users doing adhoc queries

Run StarRocks on top of raw data and then create views or materialized views as needed.

AirBnB with StarRocks: 4 JOINS with billions of rows in under 4 seconds

Tencent Games with StarRocks: 400+ users doing ad hoc queries on xx+ petabytes of data on Apache Iceberg files.

Here are some specific examples of how StarRocks is being used by fintech companies:

• Fraud detection: StarRocks can be used to detect fraud in real time by analyzing transaction data for suspicious patterns. This can help fintech companies to prevent fraud and protect their customers’ accounts.
• Risk management: StarRocks can be used to assess risk in real time by analyzing factors such as customer credit history, transaction history, and market conditions. This can help fintech companies to make informed decisions about lending and other financial services.
• Real-time trading: StarRocks can be used to support real-time trading by providing traders with access to the latest market data and analytics. This can help traders to make better trading decisions and improve their profitability.

Overall, StarRocks is a powerful and versatile database that is well-suited for fintech applications. It offers real-time analytics, scalability, and flexibility, making it a good choice for fintech companies of all sizes.

Read more about StarRocks at http://starrocks.io

StarRocks, a Linux Foundation project, is a next-generation sub-second MPP OLAP database for full analytics scenarios, including multi-dimensional analytics, real-time analytics, and ad-hoc queries. StarRocks received InfoWorld’s 2023 BOSSIE Award for best open source software.