Google Cloud Memorystore vs Redis
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Detailed Comparison
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams. | Cloud Memorystore for Redis provides a fully managed in-memory data store service built on scalable, more secure, and highly available infrastructure managed by Google. Use Cloud Memorystore to build application caches that provides sub-millisecond data access. Cloud Memorystore is compatible with the Redis protocol, allowing easy migration with zero code changes. |
| - | Less DevOps, More Code - Spend more time writing code that takes advantage of the power of Redis and less time managing Redis. Cloud Memorystore automates complex tasks like enabling high availability, failover, patching, and monitoring so that you can spend more time coding.; Scale as Needed - With Cloud Memorystore for Redis, you can easily achieve the sub-millisecond latency and throughput your applications need. Start with the lowest tier and smallest size, and then grow your Redis instance effortlessly with minimal impact to application availability. Cloud Memorystore can support instances up to 300 GB and network throughput of 12 Gbps.; Highly Available - High availability instances are replicated across two zones and provide a 99.9% availability SLA (when generally available). Instances are monitored constantly, and with automatic failover, applications experience minimal disruption.; Google Grade Security - Cloud Memorystore instances are isolated and protected from the internet using private IPs and are further secured using IAM role-based access control.; Easy Lift and Shift - Cloud Memorystore for Redis is Redis protocol compatible. You can lift and shift your applications from open source Redis to Cloud Memorystore without any code changes. There is no need to learn new tools since all existing tools and client libraries just work. |
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What are some alternatives to Redis, Google Cloud Memorystore?
Hazelcast
With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.
Aerospike
Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.
MemSQL
MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.
Apache Ignite
It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale
SAP HANA
It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.
Redis To Go
Redis To Go was created to make the managing Redis instances easier, whether it is just one instance or serveral. Deploying a new instance of Redis is dead simple, whether for production or development.
VoltDB
VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.
Redis Cloud
Redis Cloud is a fully-managed service for running your Redis dataset. It overcomes Redis’ scalability limitation by supporting all Redis commands at any dataset size. Your dataset is constantly replicated, so if a node fails, an auto-switchover mechanism guarantees data is served without interruption.
Tarantool
It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications
Azure Redis Cache
It perfectly complements Azure database services such as Cosmos DB. It provides a cost-effective solution to scale read and write throughput of your data tier. Store and share database query results, session states, static contents, and more using a common cache-aside pattern.
