Infinispan
Infinispan is an open source in-memory data grid and distributed cache. It is used to store and retrieve data with microsecond response times, while providing data reliability and availability.
Infinispan: Open Source In-Memory Data Grid & Distributed Cache
Infinispan is an open source in-memory data grid and distributed cache. It is used to store and retrieve data with microsecond response times, while providing data reliability and availability.
What is Infinispan?
Infinispan is an open source in-memory data grid and distributed cache written in Java. It offers extremely low latency and high availability for accessing data while also providing data reliability and resilience against failure.
Infinispan works by distributing data across a cluster of servers running Infinispan nodes. The data is held in memory to ensure microsecond response times for accessing and updating the data. The nodes replicate the data to protect against server failures or network partitions.
Key capabilities and use cases of Infinispan include:
- Distributed in-memory cache for boosting performance of data access
- Compute grid for parallel processing and scaling out data-intensive workloads
- Event stream processing with low publish and subscribe latencies
- Storage for fast access to transient data that can be recovered if nodes fail
Infinispan offers powerful querying, MapReduce based distributed processing, transactions, and event streaming on the stored data. It is scalable to hundreds of servers and petabytes of in-memory data. Popular usage scenarios include holding session data, user profiles, temporary data, and more.
Infinispan Features
Features
- Distributed in-memory key/value data store
- Supports transactions
- Data partitioning
- Data replication
- Persistence to disk or database
- Querying and indexing
- Caching for databases
- Clustering and high availability
Pricing
- Open Source
Pros
Very fast data access
Scalable and elastic
Fault tolerant
Supports many data structures
Integrates with many frameworks/platforms
Open source with large community
Cons
Complex to configure and operate
Not ideal for durable long-term storage
Can be resource intensive
Not as fully featured as some proprietary options
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