Azure Cosmos DB vs Hazelcast

Struggling to choose between Azure Cosmos DB and Hazelcast? Both products offer unique advantages, making it a tough decision.

Azure Cosmos DB is a Ai Tools & Services solution with tags like nosql, document-database, microsoft-azure, cloud-database.

It boasts features such as Globally distributed database, Multiple data models (document, key-value, wide-column, graph), Automatic indexing and querying, Multi-master replication, Tunable consistency levels, Serverless or provisioned throughput, SLAs for high availability, Encryption at rest and in transit and pros including High scalability and availability, Low latency worldwide access, Multiple APIs and SDKs, Automatic indexing and querying, Flexible data models, Serverless option reduces ops overhead.

On the other hand, Hazelcast is a Development product tagged with caching, processing-streams, clustering.

Its standout features include Distributed in-memory data store, Low latency data access, Automatic sharding and rebalancing, ACID transactions, Querying and aggregation, Event journaling, Multi-datacenter replication, Web session clustering, Continuous query, Machine learning, and it shines with pros like Fast performance, Easy scalability, High availability, Flexible deployment options, Open source, Rich ecosystem.

Feature	Azure Cosmos DB	Hazelcast
Overall Score	N/A	N/A
Primary Category	Ai Tools & Services	Development

Product Overview

Azure Cosmos DB

Description: Azure Cosmos DB is a globally distributed, multi-model database service by Microsoft for mission-critical applications. It supports document, key-value, wide-column, and graph databases, and provides APIs for multiple platforms.

Hazelcast

Description: Hazelcast is an open source in-memory data grid that enables distribution of data and computation across servers for scalability, speed, and resilience. It is commonly used for caching, processing streams, and clustering.

Key Features Comparison

Azure Cosmos DB Features

• Globally distributed database
• Multiple data models (document, key-value, wide-column, graph)
• Automatic indexing and querying
• Multi-master replication
• Tunable consistency levels
• Serverless or provisioned throughput
• SLAs for high availability
• Encryption at rest and in transit

Hazelcast Features

• Distributed in-memory data store
• Low latency data access
• Automatic sharding and rebalancing
• ACID transactions
• Querying and aggregation
• Event journaling
• Multi-datacenter replication
• Web session clustering
• Continuous query
• Machine learning

Pros & Cons Analysis

Azure Cosmos DB

Pros

• High scalability and availability
• Low latency worldwide access
• Multiple APIs and SDKs
• Automatic indexing and querying
• Flexible data models
• Serverless option reduces ops overhead

Cons

• Can be more expensive than other databases
• Steep learning curve for some features
• Limited query support compared to SQL databases
• Vendor lock-in

Hazelcast

Pros

• Fast performance
• Easy scalability
• High availability
• Flexible deployment options
• Open source
• Rich ecosystem

Cons

• Complex configuration
• Steep learning curve
• No visual interface

Pricing Comparison

Azure Cosmos DB

• Pay-As-You-Go
• Subscription-Based

Hazelcast

• Open Source
• Enterprise Edition (Subscription)