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Redise Cloud

Secure, highly available Redis as a hosted, fully managed cloud service

Feature / Function

Redis Cloud
Redis Cloud
ElastiCache
ElastiCache
RedisGreen
Azure Redis Cache
RedisToGo
RedisToGo
RedisGreen
RedisGreen
ObjectRocket
Object Rocket
Heroku Redis
Heroku Redis
Compose.io
Compose.io
General
Main use case Database,
Cache
Cache Cache Cache Cache Cache Cache Cache
Service Type Serverless Instance-based Instance-based Instance-based Instance-based Instance-based Instance-based Instance-based
Multiple databases per plan, each running as a dedicated process and in a non-blocking manner Yes No No No No No No No
High Availability
In-zone replication Yes Yes Yes No Yes Yes Yes Yes
Multi-zone replication Yes Yes No No No No No No
Auto fail-over Seconds Minutes Minutes No No Minutes No No
Data persistence AOF every 1 sec,
Snapshot
No Durability is not guaranteed No Maybe Maybe Yes Yes
Backup Periodic,
Ad-hoc
Periodic,
Ad-hoc
Yes Periodic Periodic Periodic No Periodic,
Ad-hoc
Scalability
Clustering support Yes Yes Fixed size cluster No No No No No
Sharding By Hash-Tag
or RegEx
By Hash-Tag By Hash-Tag No No No No No
Infinite & auto-scalability Yes No No No No No No No
Elasticity - dynamically grow & shrink Yes No No No No No No No
Performance
Responsive to high loads, "noisy neighbours" or instance size Yes No No No No No No No
No performance degradation during AOF Rewrite or Snapshot Yes No No No No No No No
Built-in acceleration features: socket connections, connection pooling, pipelining Yes No No No No No No No
Maximum database connections Unlimited 65,000 10,000 Unlimited Limited Unlimited 5,000 5,000
Security
AWS Security Group Yes Yes N/A No No N/A No No
SIP authentication Yes No No No No No No No
SSL Authentication & Encryption Yes No Yes No No Yes Yes No
Redis password Yes No Yes Yes Yes Yes Yes Yes
Ops
No data loss on plan upgrade Yes No No No No No No No
Fully automated service throughout dataset lifecycle Yes No No No No No Yes No
Offerings
Pay-as-you-go plan Yes No No No No No No No
Reserved instances Yes Yes No No No No No No
Dedicated instances Yes Yes Yes No Yes No Yes No
Availability
Clouds AWS; GCP; Azure;
IBM SoftLayer
AWS Azure AWS AWS Rackspace AWS AWS; GCP
Regions AWS/us-east-1;
AWS/us-west-2,
AWS/eu-west-1,
AWS/northeast-1;
AWS/southeast-1;
AWS/southeast-2;
Azure/us-east;
Azure/us-west;
GCP/us-central1;
IBM SoftLayer/Dallas
AWS Azure AWS/us-east-1 AWS/us-east-1;
AWS/eu-west-1
Rackspace
US-EAST
AWS/us-east-1;
AWS/eu-east-1
AWS/us-east-1;
AWS/eu-east-1;
GCP/us-east-1;
GCP/eu-east-1
Service guaranteed from the same AWS zone as your app servers Yes Yes N/A No No N/A No No
Platforms-as-a-Service Heroku;
IBM BlueMix;
Azure Store;
CloudFoundry;
OpenShift;
dotCloud;
AppFog;
AppHarbor;
None None Heroku;
AppHarbor;
Engine Yard /
Orchestra
Heroku None Heroku IBM BlueMix

The Key Differentiator Between Redise Cloud and Other Hosted Redis Services

Most hosted services offer standard cloud instances pre-loaded with open source Redis. This approach does not tackle the operational limitations of running Redis on the cloud and does not provide great advantage over the do-it-yourself approach.

Redise Cloud overcomes these limitations by adding the breakthrough Redise technology layer to open source Redis, while fully supporting it. This superior approach is what makes Redise Cloud exceptional when it comes to high availability, performance and scaling. The technology virtualizes multiple cloud servers into an infinite pool of memory, consumed by users according to the actual size of their datasets.

A dataset is distributed in small chunks across multiple shards and multiple nodes, minimizing the recovery time from a node failure.

Datasets are also constantly replicated, so if a node fails, an automatic failover mechanism guarantees data is served without interruption.

Redise Cloud supports various data persistence options without compromising on data integrity, throughput or low latency. Users can also back up their datasets to a remote persistent storage for disaster recovery purposes.

With Redise Cloud, scaling is performed automatically – the shards autonomously inflate, deflate, multiply or reduce according to the dataset size and the measured performance of each shard. A dataset can continuously grow from a few megabytes to gigabytes, terabytes and even petabytes, meeting any Redis scalability needs.

Redise Cloud is completely “zero touch.” A Redis database can be created in seconds, and all operations are fully-automated from that moment on.