ITTIA's M2M solution offers embedded system developers an easy way to connect applications and communicate information. For example, a home automation application can monitor the cycle of a washing machine, schedule a coffee machine to finish brewing at a specific time, and check that lights are off when away from home. Residents need to access and control information on these devices through multiple interfaces, whether mounted in the home or on a personal smart phone or tablet. A database for such devices must provide a framework for communication within the M2M infrastructure.
Developers of embedded applications such as medical devices,
industrial automation, automotive software, etc. often need to deal with
serious data management issues in which a large amount of data needs to
be analyzed with typical queries by end users of the applications that
they are building. These embedded ecosystems are composed of devices
that divide up Big Data problems.
Some data is isolated to each
device, while other data is shared with select peers. ITTIA DB SQL's
unique replication and synchronization features offer to efficiently
Applications for embedded systems – including medical devices, industrial automation, automotive software, and mobile tablets – often encounter serious data management challenges in which a large amount of data is collected and accumulated at different locations. Typical queries required by end users of these systems are not easily met.
With ITTIA DB SQL a large data set can be distributed across a wide array of devices, with the potential to store millions of rows per device.
Data management and query analysis are important criteria for interacting with embedded data. ITTIA DB SQL offers embedded developers two independent methodologies for managing and running queries: SQL and direct low-level access. Benefits include performance tuning, speedy query execution, code simplicity, and reduced overhead when detouring around SQL. These rich APIs provide flexibility for embedded developers.
ITTIA DB SQL is designed to aid developers of applications for embedded systems and devices to store persistent data with three important factors in mind: reliability, scalability, and shared access. Our database meets these important principals through transaction logging, indexed search, and row-level locking.
Developers of applications for embedded systems and devices often ask us
whether they should consider On-Disk or In-Memory database engines. My
answer is: select a Hybrid database, which offers the best of the both
worlds. With In-Memory, you use memory tables for high-performance
including frequent updates and small-table select. On the other hand,
with On-Disk, you can use disk tables to insert at high throughput and
effeciently select from very large tables. ITTIA DB SQL is a hybrid
database; memory and disk tables are interchangeable and you benefit
Managing "big data" is an interesting challenge. When data becomes
too large to fit on a single system, characteristics such as volume,
throughput and variety become important. On the other hand, consistency
and isolation become more difficult to accomplish, especially as data is
often replicated to different physical locations.
Finding ways to decrease health care cost is a real problem and an interesting political topic. While thousands are scratching their heads to determine how to reduce cost of healthcare for humans, one of our customers in Europe has already done so for livestock. Using robots to monitor and manage animal health care, vital information about feeding habits is stored and managed in an ITTIA DB SQL database embedded in the robot. Administrators analyze this data to significantly increase yields and/or reduce inputs through programmable animal feeding strategies.
Qt 5 is a major renovation that improves platform support,
formalizes QtQuick, and introduces many architectural improvements. SQL
driver notification signals now include a payload, which ITTIA DB SQL
leverages to send data change notification events to application tasks,
complete with a copy of the modified data. In this way, our embedded
database provides a convenient way to send
messages between applications and threads that are actively
sharing the
same database.
