Built-in high availability provides automatic failover and replication, plus active-active and active-passive geographic distribution options for minimal downtime.
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Redis vs. Hazelcast
You know Redis for caching, but Redis is so much more than just fast speeds. Redis is the industry leader in innovation. Engineered to be simpler yet faster than the rest, Redis delivers consistent, real-time performance at any scale.
How Redis and Hazelcast compare
| Hazelcast | |||
|---|---|---|---|
| Build | |||
| Build | Boost app performance as a cache | ||
Full persistence and durability | |||
Advanced session management with hash field expiration (HFE) | — | ||
Real-time data ingestion and event-driven architecture | |||
Distributed data processing engine | — | ||
Automatic ingestion and change data capture (CDC) of source databases (including Oracle, postgres, MySQL, etc.) | — | ||
Built-in SQL support | — | ||
Built-in JSON support without serialization or external processing needed | — | ||
Streaming support for events and data ingestion | |||
Full text search and secondary indexing | — | ||
Built-in time series support for efficiently storing and querying time-stamped data | — | ||
Probabilistic data structures (Bloom, top-k, t-digest, etc.) for memory-efficient approximations | — | ||
Consumer groups for scalable, distributed message consumption with automatic failover and load balancing | — | ||
Vector database for retrieval augmented generation (RAG), semantic caching, and other GenAI & ML use cases | —Beta | ||
Rapid development with out-of-the-box object mapping libraries for various programming languages and frameworks | —Limited
(Java focused) | ||
End-to-end support with language-specific client libraries | Jedis, Lettuce, redis-py, redisVL, NRedisStack, node-redis, and go-redis | —Java focused | |
User interface including tutorials, a copilot, and a query builder | Redis Insight | — | |
| Deploy | |||
| Deploy | Runtime environment that may require management, garbage collection, and tuning | —None | —Java Virtual Machine (JVM) |
Fully supported on-premises, in the cloud, or in hybrid environments | |||
Automated deployment on any cloud or multi-cloud | |||
Serverless as-a-service offering without manual management | — | ||
Deploy multiple datastores in a single cluster for resource efficiency (multi-tenancy) | — | ||
Extend in-memory capacity using SSD storage through data tiering |  Redis Flex | — | |
| Run | |||
| Run | Transform slow data into real-time data by ingesting data from external databases in real-time | Redis Data Integration (RDI) | — |
Deliver consistent, real-time customer experiences globally with geo-distributed (active-active) datastores | |||
Conflict free replicated data types (CRDTs) for automatic conflict management and strong consistency | — | ||
Automated database and cluster management (scaling, re-sharding, rebalancing) | — | ||
Automated hitless upgrades | —Blue-green clusters | ||
Built-in disaster recovery management | Automated | —Manual | |
Enterprise-grade customer support | |||
| Secure | |||
| Secure | Access control lists (ACLs) and role based access control (RBAC) for data access | ||
Role based access control (RBAC) per command | — | ||
Centrally managed RBAC | — | ||
LDAP integration for identity management and role assignment | |||
HashiCorp Vault support | |||
Connection and authentication auditing | — |
A closer look at the features
Offers replication and fault tolerance but risks split-brain scenarios under certain conditions.
Supported data types
| Hazelcast | |||
|---|---|---|---|
| Strings | |||
| Strings | Any sequence of bytes, such as a simple string or a serialized object | ||
| Hashes | |||
| Hashes | Collections of key-value pairs | — | |
| JSON | |||
| JSON | Queryable JavaScript Object Notation (JSON) documents | —String only | |
| Lists | |||
| Lists | Linked lists of strings | ||
| Sets | |||
| Sets | Unordered collections of strings | ||
| Sorted Sets | |||
| Sorted Sets | Collections of strings sorted by score | — | |
| Bitmaps | |||
| Bitmaps | Strings treated like bit vectors | — | |
| Geospatial Indexes | |||
| Geospatial Indexes | Data for storing and querying geographic locations | — | |
| Streams | |||
| Streams | An enhanced append only file for streaming data | ||
| Time series | |||
| Time series | Data designed to store sequences of data points indexed by time | — | |
| Bloom | |||
| Bloom | A probabilistic data structure that checks for presence of an element in a set | — | |
| Top-k | |||
| Top-k | A probabilistic data structure that allows you to find the most frequent items in a data stream | — | |
| HyperLogLog | |||
| HyperLogLog | A probabilistic data structure that estimates the cardinality of a set | — |
Key Redis features and capabilities
Active-active
geo-distribution
Seamless global data distribution with strong consistency.
Multi-tenancy
Efficient resource utilization with support for multiple datastores in a single cluster.
Query and search
Scalable query and search capabilities make apps more dynamic and interactive.
Redis Data Integration
Automatically connect Redis with other data sources to move and sync data seamlessly across your architecture.
Client support
We offer full end-to-end support for official clients including Jedis, node-redis, redis-py, NRedisStack, Go-Redis, Lettuce, and more.
Get started
Speak to a Redis expert and learn more about enterprise-grade Redis today.