McObject LLC

Is your embedded database silently shortening the life of your NAND flash?

A small database update can create several times more physical writes - a problem known as write amplification. Over time, this increases flash wear, reduces device lifespan, and raises the total cost of the
system.

This article explores how database architecture, flash utilization, transaction length, and cache size affect
NAND writes.

A valuable read in Embedded.com for embedded developers and system architects.

https://t.ly/Hidden_Cost

Q) Is eXtremeDB/rt available for certified versions of RTOS?
A) Yes. eXtremeDB/rt is available for selected safety- and security-certified RTOS environments, including DEOS, LynxOS-178, VxWorks 653 and INTEGRITY-178B. Certification applies to the underlying RTOS; eXtremeDB/rt is provided for use in these environments.

Learn more: https://t.ly/RT_DBMS

eXtremeDB offers a Java Native Interface (JNI) for the fastest possible embedded database solution in Java. The JNI reduces development time and accelerates run-time performance in Java applications, outperforming object-relational database management systems and “pure” Java object databases, as well as object caching software in Java. eXtremeDB is also available as a classic client/server SQL RDBMS for Java (and other languages).
Learn more: https://t.ly/DBMS-4-JAVA

eXtremeDB/rt is the first and only deterministic embedded database management system for mission-critical hard real-time applications demanding an RTOS. Learn more: https://t.ly/HARD-real-time

Are you targeting an RTOS in your development? Learn more about the only *hard* real-time commercial off-the-shelf DBMS, eXtremeDB/rt. Offering real-time certainty, native integration with leading RTOS platforms and optimized flash memory access, it empowers mission-critical applications with absolute predictability and fail-safe reliability.

Learn more: https://t.ly/RTOS-DBMS

Great short read about the latest AI data management by our own Steven Graves.

AI Database Management: ANN Indexes for Resource-Constrained Devices A new class of embedded AI is emerging, where microcontrollers run vector search once reserved for servers. How can hybrid ANN indexing turn tiny, flash‑bound devices into fast...

We invite you to read, "How eXtremeDB ANN indexes and time series / sensor data fusion work together". https://t.ly/AI_timeseries

Learn how to supercharge your AI edge applications by combining time-series processing with native HNSW and Vamana ANN indexes directly inside small footprint eXtremeDB. eXtremeDB allows developers to pipeline multi-rate sensor data into normalized feature vectors for low-latency anomaly detection and pattern matching. By keeping all vector storage, time-series history, and similarity searches local to the device, you eliminate the need for a separate vector database or cloud dependencies.

Learn what gives eXtremeDB the lowest possible latency and features it offers to optimize times series data. https://t.ly/LSF1Z

for