Embedded Database Solution
With the growth of mobile and edge computing in the market, data management is playing an increasingly critical role. Raima Database Manager is designed to meet the need of OLTP and in-memory embedded applications.
Today, businesses face the challenge of an accelerating pace of business on the edge, where real-time decisions on input from multiple devices are critical. Today´s organizations demand to have everything immediately. Raima Database Manager has been created for applications that need real-time and reliable data.
With the increased deployment of Flash and SSD medium in the embedded market space, minimal writes to the media are important to deliver high performance and, at the same time, make sure that the medium lifetime is extended. Raima is one of the few embedded database vendors that have this functionality built in.
Raima´s modular architecture is designed to meet the complex architecture of future embedded applications.
Raima Database Manager Performance
Raima Database Manager sets a new performance threshold for embedded databases. Designed to address future technology demands, it provides the highest-functioning database solutions for resource-constrained environments. Raima Database Manager includes these major features: in-memory support, compression, optimized file format, snapshot, encryption, SQL, SQL PL and platform independence – we like to describe Raima as: “develop once, deploy anywhere.”
Raima´s SQL implementation has been designed for embedded systems applications. It provides a subset of the ANSI/ISO standard SQL that is suitable for running on a wide variety of computers and embedded operating systems, many of which have limited computing resources.
Scalable and responsive
RDM is an ideal solution for edge computing.
- Raima´s new release permits replicating edge information to the cloud, either to a different Raima database solution or to other cloud-based databases such as Oracle, DB2 and PostgreSQL.
- Many competitors can replicate only to other instances of their own database; here, Raima holds the competitive edge.
- Multithreading, multiprocessing, parallel operations with lower power consumptions are important to embedded applications for scalability reasons.
- Scalable and responsive, Raima permits data and applications to be placed near the source; it’s an IoT solution that addresses edge-of-the cloud needs.
Decreased Time to Market
RDM’s architecture delivers the highest performance while simultaneously safeguarding data and maintaining full ACID compliance.
- For in-memory databases, Raima uses a completely unique internal format to take full advantage of the direct memory characteristics of random access, zero latency, etc.
- If the database is on disk, Raima instead uses another uniquely designed and optimized format to take into consideration the latency involved with disk usage.
- The new architecture also hides hardware platform specifics such as byte ordering in the new file format design, freeing developers to focus on other details.
Because Raima is automated to manage the database storage, it does not require administration to increase the size of the database or its underlying objects.
Essentially all of the critical functions are self-managed, so customers do not require a dedicated DBA. It’s an ideal solution for users who don’t have high-level technical skills because so little administration and maintenance is required.
Raima´s Embedded Database on the Edge
Raima´s maintenance-free, embedded database solution installed on edge computing devices provides the missing link to more efficient data collection and allows for quicker decisions. A database on the edge selectively moves computing, storage, communication, control and decision making closer to the network edge, where data is being generated, to solve the limitations in the current infrastructure, enabling mission-critical, data-dense use cases.
Embedding a database on edge computing devices can allow clients to more efficiently work with a cloud back-end system like Amazon AWS by taking advantage of data movement technology within the database itself. Selective data can be synchronized in near real-time up into the cloud system (e.g., business analytics). This will be done only after the data has been computed and summarized on the edge, so only relevant data pass over the network to the cloud.
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