InfiniSpan

Additional features

Open-Source In-Memory Database

The core identity of the product, highlighting its open-source nature and primary storage in RAM.

Holds Nearly Any Type of Data

Capable of storing diverse data formats, from plain text to structured Java objects.

Lightning-Fast Data Retrieval

Achieves high performance due to its in-memory nature and optimized access.

Powerful Full-Text Search

Allows for comprehensive text-based queries across stored data.

Vector Search Capabilities

Supports searching based on vector embeddings, useful for AI/ML applications and similarity searches.

Reliability and Integrity Guarantee

Ensures data consistency and correctness.

Distributed Across Elastically Scalable Clusters

Data is spread across multiple nodes that can be added or removed dynamically to scale capacity.

High Availability

Designed to minimize downtime and ensure continuous data access.

Fault Tolerance

Resilient against node failures, preventing data loss.

Cross-Site Replication

Ability to replicate data between multiple geographic sites for disaster recovery and global clusters.

Native, High-Performance Protocol (Hot Rod)

A custom binary TCP protocol optimized for Infinispan client-server communication.

Redis Client Compatibility

Allows connecting to Infinispan using standard Redis clients and commands.

Memcached Client Compatibility

Allows connecting to Infinispan using standard Memcached clients.

Available as a Java Library

Can be embedded directly into Java applications for co-located data storage.

Infinispan Server for Remote Access

Provides an independent data layer for applications to connect remotely with in-memory performance.

Consistent Hashing Techniques

Used to efficiently locate data within the cluster, minimizing network hops.

HTTP Client Access

Supports connecting via HTTP.

Boosts Application Performance

Stores data closer to processing logic to reduce latency and increase throughput.

Shared Store for Stateful Data (e.g., HTTP Sessions)

A common use case for externalizing sessions from application heaps.

Kubernetes Operator Support

Facilitates deployment and management in Kubernetes environments like Red Hat OpenShift.

Hybrid and Multi-Cloud Deployments Ready

Cross-site replication capabilities enable complex cloud strategies.

Data Consistency with Concurrent Writes (Cross-Site)

Guarantees data accuracy even with concurrent writes across asynchronously replicated sites.

Open-Source License (Apache 2.0)

Governed by a permissive open-source license, encouraging contributions.

Community and Blog

Active community and regular blog updates on new features and use cases.

Use Case Integrations/Extensions

Quarkus extensions

Spring and Spring-Boot integration

Keycloak integration (often used for session management)

Langchain & Langchain4j (for AI applications)

Hibernate (as a second-level cache)

Apache Camel

Micronaut

Wildfly (application server)

Vert.x

Kogito

Management & Monitoring (Implied)

While not explicitly detailed, a distributed system of this scale would have tools for management and monitoring.

Puggable Cache Stores (Implied from external sources)

Can persist data to various external stores like JDBC databases, file systems, S3, MongoDB, Cassandra, HBase for "warm starts" or overflowing data.

Off-Heap Storage (Implied from external sources)

Can store data outside the JVM heap to reduce garbage collection overhead and manage larger datasets.

Distributed Code Execution

Allows pushing processing logic to where the data resides for efficient computation (e.g., MapReduce-like operations via Java Stream API).