inMemory+ primarily relies on main memory for computer data storage. It is contrasted with database management systems that employ a disk storage mechanism. Main memory databases are faster than disk-optimized databases because the internal optimization algorithms are simpler and execute fewer CPU instructions. Accessing data in memory eliminates seek time when querying the data, which provides faster and more predictable performance than disk-based systems.
inMemory+ is the distributed in-memory database that provides real-time analytics on Big Data, empowering organizations to:
- Make data-driven decisions.
- Better engage customers.
- Discover competitive advantages.
Yes, inMemory+ provides standard SQL support. Users can use familiar SQL query syntax to do data operations. No special language syntax is needed to use this product.
Sharding is a type of database partitioning that is used to separate very large databases into smaller, faster, more easily managed pieces called data shards.
Yes, inMemory+ provides the capability to scale out and shard data to any number of nodes.
Range sharding - You define the ranges and data is distributed according to the range policy.
Count sharding - In this approach, the number of records permitted on any node is defined.
Auto memory - Data starts accumulating on first available slave, when data exceeds the configured memory limit, then it starts residing on the next available node.
By using control panel you can build your cluster having master node and slave node.
Yes, inMemory+ provides easy and flexible UI to manage data operations.
Yes, through UI and navigating to error screen you can see all application logged errors.
Yes, inMemory+ provides user authentication and authorization for security purpose.
inMemory+ exposes different service interfaces e.g. TCP channel, http interface. You can use any of these service interfaces to communicate with inMemory+.
By using Synchronizer, you can import data into it.
By using Synchronizer, you can export data from inMemory+.
SQL Server, Excel, Access, XML, and CSV.
Business users, business management, information consumers, business intelligence analysts, data scientists, information technology, database administrators, cloud operators, etc.
Organizations that are experiencing performance and scaling problems with their applications and/or want to deploy and scale-out efficient robust cost-effective applications.