In-memory databases (IMDBs) and in-memory data grids (IMDGs) are technologies that cater to high-speed data management, but they have distinct use-cases and characteristics:
An in-memory database (IMDB) is a type of database that utilizes main memory for data storage to achieve faster performance since accessing data in memory is much faster than disk-based storage. They are well-suited for applications demanding very short response times such as telecommunications network equipment and mobile advertising platforms.
Example: Redis, SAP HANA
import redis # setup connection r = redis.Redis(host='localhost', port=6379, db=0) # set key-value pair r.set('foo', 'bar') # retrieve value by key print(r.get('foo')) # Output: b'bar'
An in-memory data grid (IMDG) is a middleware distributed data storage system where data is stored across multiple servers and provides low response time, high availability and scalability. They are particularly useful in applications requiring real-time processing of live data streams and large-scale data processing.
Example: Hazelcast, Apache Ignite
import com.hazelcast.core.Hazelcast; import com.hazelcast.core.HazelcastInstance; // Create a Hazelcast Instance HazelcastInstance hz = Hazelcast.newHazelcastInstance(); // Get a Distributed Map Map<String, String> map = hz.getMap("my-distributed-map"); // Put elements to the map map.put("key", "value"); // Get the element from the map System.out.println("Key:Value => " + map.get("key")); // Output: value
Differences:
Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.