For a lightweight in-memory store for transient data, the strongest matches are snapchat/keydb (KeyDB is a multithreaded, Redis-compatible in-memory key-value store and), redis/redis (Redis is the definitive in-memory key-value data store, purpose-built) and microsoft/garnet (Garnet is a multi-threaded Redis-compatible in-memory key-value store with). tporadowski/redis and microsoft/faster round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
We curate open-source GitHub repositories matching “transient state stores”. Results are ranked by relevance to your query — pick filters below to narrow, or refine with AI.
KeyDB is a multithreaded in-memory key-value store and distributed cache. It functions as a NoSQL database utilizing multi-version concurrency control to execute non-blocking queries and scans. The project is a multithreaded fork of Redis that maintains protocol compatibility while utilizing a multithreaded architecture to scale across multi-core hardware. It distinguishes itself with flash-tiered storage, allowing the system to offload data from primary RAM to SSD or flash storage to increase total capacity. The system supports high availability through active-active mesh replication and mu
KeyDB is a multithreaded, Redis-compatible in-memory key-value store and distributed cache that supports TTL-based expiration, active-active replication for failover, atomic operations, multiple persistence options, and wide client language support via the Redis protocol, making it a comprehensive flagship choice for caching and session management.
Redis is an in-memory, key-value database designed to provide sub-millisecond latency for read and write operations. It functions as a versatile data platform, serving as a distributed cache, a message broker, a NoSQL document store, and a vector database. The system utilizes an event-driven, single-threaded loop to process requests efficiently, while maintaining data durability through append-only persistence logs and asynchronous snapshotting mechanisms. What distinguishes Redis is its ability to handle complex data structures—including strings, hashes, lists, sets, and sorted sets—alongsid
Redis is the definitive in-memory key-value data store, purpose-built for caching, session management, and fast lookups, with comprehensive support for TTL expiration, replication, failover, atomic operations like INCR/DECR, persistence options, and multi-language clients — it fully matches every aspect of this search.
Garnet is a multi-threaded in-memory database and distributed key-value store. It functions as a high-performance remote cache store that implements the RESP wire protocol to maintain compatibility with existing Redis clients and libraries. The project is distinguished by a shared-memory architecture that enables parallel request processing across multiple cores for sub-millisecond latency. It features a tiered storage system that automatically offloads colder data from system memory to SSD or cloud storage layers, and includes a specialized vector search database for high-dimensional similar
Garnet is a multi-threaded Redis-compatible in-memory key-value store with built-in replication, atomic operations, TTL support, and persistence, making it a comprehensive fit for temporary caching, session management, and fast lookups.
Redis is a high-performance in-memory key-value store that functions as a distributed cache, message broker, and NoSQL database. It provides sub-millisecond read and write access to data stored in RAM and can operate as a vector database for indexing high-dimensional embeddings. The system supports a wide range of data storage and synchronization primitives, including the management of strings, hashes, lists, sets, and JSON documents. It enables real-time data operations through atomic transactions, hybrid persistence using snapshots and append-only logs, and high-availability configurations
Redis is a high-performance in-memory key-value store that provides all the features you need for caching and fast data access, including TTL expiration, replication, atomic operations, and persistence, with client libraries for almost every language.
FASTER is a high-throughput key-value store that combines an in-memory data store with a hybrid memory-disk storage engine, enabling datasets larger than available RAM. It uses a latch-free, cache-optimized index for concurrent point lookups and heavy updates, and records all mutations to a persistent append-only log on disk with checksum validation and group-commit checkpointing for crash recovery. The system supports multi-key transactional workloads through atomic multi-key locking, ensuring transactional consistency without coarse-grained contention. It exposes the key-value store to remo
FASTER is a high-throughput embedded key-value store that combines in-memory caching with a persistent hybrid engine, making it a solid fit for fast lookups and session storage, but it lacks explicit TTL-based expiration and built-in replication, so it is narrower than a full caching solution like Redis.
Valkey is an in-memory, NoSQL database server designed for high-performance data storage and real-time state management. It operates as a distributed key-value store, maintaining datasets entirely within system memory to facilitate sub-millisecond response times for read and write operations. The system distinguishes itself through a single-threaded event loop that utilizes asynchronous I/O multiplexing to ensure high throughput. It supports high availability via master-replica replication and provides a decoupled communication model through a built-in publish-subscribe messaging pattern. To
Valkey is an in-memory key-value store that supports replication, TTL expiration, atomic operations, data persistence, and multi-language clients, making it a comprehensive match for caching and session management needs.
DiceDB is a distributed cache manager and hierarchical storage engine based on a Valkey key-value store. It functions as a high-availability key-value cluster that balances performance and cost by distributing data across memory and disk tiers. The system supports working sets larger than available RAM by persisting evicted keys to disk and restoring them on demand. It also includes a real-time query subscription system that notifies clients when data matching specific criteria is updated. The project provides distributed cache coordination through master node health monitoring and quorum-ba
DiceDB is a distributed, high-availability key-value cache with disk persistence and real-time subscriptions, which matches your need for an in-memory cache, but its support for TTL-based expiration and atomic operations is not explicitly confirmed in the description.
Dice is a low-latency key-value store based on Valkey that functions as a hierarchical storage engine. It combines a high-speed memory store with a tiered cache system to manage data across multiple storage levels. The system extends memory capacity by implementing a disk-backed cache that automatically persists evicted items to disk and restores them during cache misses. This storage tiering balances retrieval speed and operational cost by distributing data between fast memory and slower disk storage. The engine includes a query subscription service that monitors specific data patterns and
Dice is a low-latency key-value store that combines an in-memory cache with disk-backed persistence and tiered storage, making it a straightforward fit for caching and session management; its Redis-compatible design implies support for TTL expiration and atomic operations, though built-in replication and multi-language client libraries are not explicitly confirmed in the available evidence.
Ristretto is a high-performance in-memory cache and concurrent key-value store for Go applications. It provides a thread-safe memory store that manages strict memory bounds and employs probabilistic set filters to reduce lookup overhead. The system is distinguished by an admission-policy cache that utilizes frequency sketches and cost-based eviction to maximize hit ratios. It minimizes contention and improves throughput through the use of striped ring buffers and concurrent map sharding. The project covers a broad range of data management capabilities, including time-based expiration, item f
Ristretto is a high-performance in-memory cache and concurrent key-value store for Go, offering TTL-based expiration and efficient eviction, which fits the caching intent, but it lacks replication, atomic operations, persistence, and multi-language libraries found in more complete solutions.
Dragonfly is a high-performance, multi-model in-memory data store designed to serve as a drop-in replacement for existing database infrastructures. By utilizing a multi-threaded, shared-nothing architecture and a fiber-based concurrency model, it maximizes CPU utilization and minimizes latency for read and write operations. The system supports a wide range of data structures, including strings, hashes, lists, sets, sorted sets, and JSON documents, while maintaining full compatibility with standard industry wire protocols and client libraries. What distinguishes Dragonfly is its focus on effic
Dragonfly is a high-performance, Redis-compatible in-memory data store that provides key-value caching with TTL expiration, atomic operations, persistence, replication, and works with any Redis client library, exactly matching the need for temporary in-memory storage with those features.
Olric is a distributed data grid and in-memory key-value store that partitions and replicates data across a cluster of servers. It serves as a shared memory system for managing distributed maps, performing atomic operations, and acting as an in-memory data cache. The system provides a distributed locking mechanism for concurrency control and a pub-sub messaging system that broadcasts and routes messages over named channels across the cluster. The platform covers wide-ranging capabilities including cluster management and orchestration, data replication with configurable quorums, and automated
Olric is a distributed in-memory key-value store that supports atomic operations and replication, making it suitable for caching and session management, though explicit TTL expiration and persistence features are not prominently highlighted.
Ignite is a distributed in-memory data grid and compute platform. It functions as a distributed SQL database and storage engine designed to store and process large datasets in RAM to minimize latency and increase calculation speed. The system is distinguished by a multi-tier storage engine that manages data placement across memory and disk to balance high-speed access with large capacity. It features a distributed compute grid that executes custom logic directly on the nodes where data resides to reduce network traffic. The platform provides a broad set of capabilities including ACID transac
Apache Ignite is a distributed in-memory data grid that functions as a key-value cache with TTL expiration, replication, atomic operations, persistence, and multi-language client support, squarely matching the sought in-memory data store/cache.
Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis
Hazelcast is a full-featured distributed in-memory data grid that provides low-latency key-value access, built-in replication and failover, atomic operations, TTL-based eviction, data persistence, and multi-language client libraries, making it an excellent fit for caching, session management, or fast lookup.
Memcached is a high-performance, distributed, in-memory key-value storage and request routing engine. It functions as a volatile data store designed to accelerate dynamic applications by caching objects in RAM, thereby reducing backend database load and providing sub-millisecond response times. The system utilizes a specialized architecture that organizes memory into fixed-size slabs to minimize fragmentation and maximize throughput for high-concurrency workloads. The project distinguishes itself through a multi-threaded, lock-friendly design that scales across CPU cores and supports complex
Memcached is a high-performance distributed in-memory key-value cache that excels at caching and fast lookups with TTL expiration and atomic operations, though it lacks built-in replication/failover and data persistence, which may need external tools.
| Repository | Stars | Language | License | Last push |
|---|---|---|---|---|
| snapchat/keydb | 12.5K | C++ | BSD-3-Clause | |
| redis/redis | 74.9K | C | NOASSERTION | |
| microsoft/garnet | 11.9K | C# | MIT | |
| tporadowski/redis | 10K | C | other | |
| microsoft/faster | 6.6K | C# | mit | |
| valkey-io/valkey | 24.9K | C | other | |
| dicedb/dicedb | 10.8K | C | NOASSERTION | |
| dicedb/dice | 10.8K | C | NOASSERTION | |
| dgraph-io/ristretto | 6.9K | Go | Apache-2.0 | |
| dragonflydb/dragonfly | 30.7K | C++ | NOASSERTION |