Choosing the right database that is built for speed and scale is an important decision. While MongoDB offers general-purpose document storage, KX delivers high-performance analytics that transform how enterprises handle massive datasets.

Ready to unlock the full potential of your time-series data? Read on to see how KX compares to MongoDB.

Key differentiators: KX vs. MongoDB

KX: Independently benchmarked as the fastest in-memory, columnar analytics database available. kdb+ enables enterprises to analyze billions of live events and trillions of historical records, with a compact memory footprint and compute-efficient design that helps reduce hardware costs. Designed specifically for time-series analytics with nanosecond precision timestamps and best-in-class aggregation capabilities.

MongoDB: A general-purpose NoSQL document database that stores data in flexible JSON-like documents. While versatile for web applications and content management, it lacks the specialized optimization for time-series analytics and real-time processing that modern enterprises demand.

How KX and MongoDB compare

Survival of the fastest with KX

Modern enterprises depend on data velocity to gain a competitive advantage. Speed has evolved from a nice-to-have feature into a business requirement that determines market leadership. KX enables real-time ingestion and historical analysis across all data types, solving latency issues and providing immediate insights for better decision-making.

While MongoDB struggles with complex analytical queries that require joining and aggregating large datasets, KX’s columnar architecture delivers microsecond response times even on petabyte-scale datasets.

Precise, fast, and scale

KX’s foundation is built on three core principles that set it apart from general-purpose databases like MongoDB:

• Precision: KX delivers high-precision nanosecond timestamps, time-ordered querying, uniquely performant aggregation across flexibly defined time buckets and time-based table joins of unparalleled speed. This level of temporal accuracy is impossible to achieve with MongoDB’s document structure.
• Speed: KX enables unmatched performance for time-series data analytics with consistent sub-millisecond response times right out of the box. MongoDB, in contrast, requires complex indexing strategies and careful query optimization to achieve adequate performance.
• Scale: KX is built to scale effortlessly with the extreme data volumes, concurrency demands, and real-time requirements of capital markets and other high-throughput environments. Its tightly optimized, columnar architecture enables consistent performance as workloads grow across both historical and streaming data. While MongoDB’s schema-less design offers flexibility, it can introduce data inconsistency and architectural sprawl, making large-scale analytics deployments more complex and expensive to maintain.

Developer-friendly without compromise

KX was built for performance. Our native query language, q, is purpose-built for time-series analysis and uniquely powerful once mastered. But we recognize it has a learning curve. That’s why we’ve introduced PyKX and SQL support, giving Python developers and data scientists direct access to kdb+’s performance without needing to become q experts.

Whether you’re building real-time dashboards, running high-frequency backtests, or analyzing time-series data at scale, KX now fits more naturally into modern analytics workflows — without forcing teams to reinvent their stack.

Built for large enterprises

With over 30 years of accelerating data innovation, KX has proven itself in the world’s most demanding environments. KX’s database is regularly used in high-frequency trading (HFT) to store, analyze, process, and retrieve large data sets at high speed. This track record in financial services, where microseconds can mean millions of dollars, demonstrates KX’s ability to handle crucial workloads that would overwhelm traditional databases like MongoDB.

KX’s enterprise features include disaster recovery, automated data tiering, and seamless cloud integration. The kdb Insights portfolio provides a cloud-native analytics platform with high-performance capabilities for analyzing streaming and historical data in real time.

Success stories

Leading global banks, hedge funds, and technology companies have replaced their MongoDB-based analytics systems with KX to achieve:

• 100x faster query performance on time-series analytics compared to document databases
• 90% reduction in infrastructure costs through efficient memory utilization and compression
• Instantaneous decision-making with sub-millisecond latency for streaming data analysis
• A unified platform eliminating the need for multiple databases and analytics tools

From risk management systems processing millions of trades per second to IoT platforms analyzing sensor data from thousands of devices, KX consistently delivers performance that MongoDB simply cannot match for analytical workloads.

Schedule your demo with KX

Ready to experience the difference? See how KX can transform your data analytics or how to migrate from MongoDB while improving performance, reducing costs, and enabling new analytical capabilities you never thought possible.

Book a demo today and discover why enterprises worldwide choose KX when performance matters most.

How KX outperforms the competition