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Apache Ignite

By Author: Amar
Total Articles: 3

An in-memory computing platform called as Apache Ignite can be inputed between a user's application layer and data layer. From the current disk-based storage layer into RAM, enhancing six orders of magnitude and performance.

For handling petabytes of data to which the in-memory data capacity can be easily scaled. Both the ACID transactions and SQL queries are further supported. Scale, performance, and comprehensive capabilities far above and beyond what traditional in memory databases, data grids are offered by Ignite.

For ripping and replacing their existing databases there is no need of users for Apache Ignite. It works with NoSQL, RDBMS, and Hadoop data stores. Fast analytics, real-time streaming, high performance enabling are some of the Apache Ignite highlights. A massively parallel architecture, used a shared, affordable commodity for current or new applications power. On premises, Apache Ignite can be run and on cloud platforms like Microsoft Azure, and AWS are in a hybrid environment.

Key Features

There is an in-memory data grid for handling distributed in-memory data management and it is contained in Apache Ignite. You will find object based, ACID transactional, failover, in-memory key value store, etc. On the contrary to traditional database management systems, primary storage mechanism are used by the Apache Ignite.

Instead of disk if you are using the memory then it increase its speed upto 1 million times faster than traditional databases.
Free-Form ANSI SQL-99, compliant requires with actually no limitations is supported by Apache Ingite. There are use of any SQL function, grouping, or aggregation, and it aids distributed, noncolocated SQL joins and cross cache joins. The field queries concept of backing up to reduce the serialization and network overhead is also supported by Ignite. A computer grid for enabling parallel in memory processing is included in the Apache Ignite. There are other CPU-intensive or other resource-intensive tasks like traditional MPP, HPC, fork-join, and MapReduce processing. For Stnadard Java ExecutorService asynchronous processing is backed up by Apache.
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