MariaDB in Financial Services

Data-driven competitive edge

The financial services industry is undergoing a sea change, faced with threats from fintechs, a shift in customer preferences accelerated by the pandemic, and a patchwork quilt of regional and local regulations. Increasingly, differentiated digital capabilities are the key weapon that financial services institutions (FSIs) wield to stay ahead of their peers and new market players. FSIs depend on MariaDB to deliver database solutions that support key areas of differentiation such as high-volume transactions, fraud detection, process optimization and customer experience.

Faster Decisions

Rapidly adjust your transactional and analytical operations with cloud-native database-as-a-service (DBaaS) digital capabilities.

See Global, Act Local

Run transactions with collocated analytics in region yet keep a single centralized, common operational picture of your data with distributed SQL and columnar analytics.

Reduce Risk

Harness open source, cloud economics and innovation with the reliability, security, HA capabilities you’d expect from high-end proprietary systems like Oracle.

Factsheet

Charting a Path to Financial Services Modernization

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Customers

Customer Story

Development Bank of Singapore (DBS) migrates to MariaDB

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Customer Story

How DBAs at TradingScreen make life easier with automation

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Mariadb core FSI use cases

MariaDB products and technologies, including MariaDB Enterprise Server, ColumnStore and MaxScale, support our FSI customers across various digital capabilities to reduce costs, increase performance and scale.

High-Volume Transactions

Execute and analyze millions of transactions across multiple regions with high concurrency, security and ACID compliance for key functions such as mobile banking, card processing, wire transfers and trading.

Fraud Detection

Make more accurate decisions faster and closer to the transaction to better support key functional areas such as identity theft, account takeover prevention, credit card schemes and money laundering.

Risk Management

Perform pre- and post-transactional analytics to identify, assess and act on risks to profits, regulatory compliance, and other factors that can significantly impact operations such as loan underwriting and approvals, account transfers, and securities and market trades.

Customer Experience

Understand your customer throughout their entire lifecycle, from acquisition to retirement. Make each interaction and transaction an opportunity to cross-sell or up-sell, provide a next-best offer, and improve loyalty and reduce churn.

DISTRIBUTED TRANSACTION Capabilities

Data Integrity

Global scale across geographical regions and multiple clouds without sacrificing data integrity, maintaining full atomicity, consistency, isolation and durability (ACID).

Continuous Availability

Designed to tolerate infrastructure failures and maintain availability, storing multiple copies of data with zone awareness and multi-site replication.

Self-Managing

Continuous monitoring of data distribution and resource utilization with automated rebalancing, redistribution and re-creation of nodes and associated data to ensure highest availability and maximum performance.

Modern Analytics Capabilities

Standard SQL

Analyze large amounts of data with standard SQL, including joins with other tables (row or columnar).

Kafka and Spark Connectors

Use Kafka and Spark connectors to ingest streaming data and publish machine learning results for interactive, ad hoc analysis.

Direct Data Loading

CLI import tools as well as C, Java and Python connectors bypass the SQL layer to load data directly to storage from anywhere.

Resources

webinar

Columnar Storage + Python: Powering Modern Data Science and Analytics

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Blog Post

Analysis of Financial Time Series Data Using MariaDB ColumnStore

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Datasheet

Creating a Path to Financial Services Modernization

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Get Started

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