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Hazelcast Platform

Hazelcast Platform
Management Center
Hazelcast Cloud
Hazelcast CLC
Hazelcast Flow
Hazelcast Operator
IMDG
Tutorials

6.0-SNAPSHOT
5.5
5.4
5.3
5.2
5.1
5.0

Get started
- What’s new in 5.5
- What is Hazelcast Platform
- Ask AI
- Available versions
- Start a local cluster
  - Docker
  - CLI
  - Binary
  - Java Embedded
- Get started with Enterprise Edition
- Get started with SQL
- Get started with a Hazelcast Client
- Getting Support
Install & upgrade
Develop & build
- Architecture
- Best practices
- Member/Client Discovery
- Kubernetes
- Distributed Data Structures
  - Overview
  - Caching Data
  - AP Data Structures
  - CP Data Structures
  - Streaming Data Structures
    - Event Journal
  - AI/ML Data Structures
    - Cardinality Estimator Service
    - Vector Collection
      - Data Structure Design
      - Vector search tutorial
- Distributed Computing
  - Executor Services
  - User Code Namespaces
- Data Ingestion & Query
  - Ingesting Data from External Sources
  - Running Distributed Queries
- Building a Cache with MapStore
- Building Data Pipelines
  - About Data Pipelines
  - Get Started
    - Get Started with Stream Processing (Embedded)
    - Get Started with Stream Processing (Client/Server)
  - Ingesting Data from Sources
  - Processing Data
  - Sending Results to Sinks
    - Overview
    - Create a Custom Sink
  - Stream Processing
  - Serializing Pipelines
  - Jet Job Placement Control
  - Configuring Jobs
  - Securing Jobs
  - Submitting Jobs
  - Managing Jobs
  - Monitoring Jobs
  - Updating Jobs
  - Testing Sources and Sinks for XA Transaction Support
- SQL
  - Overview
  - SQL Over Maps
  - SQL Over Kafka
    - Tutorial
    - Mappings
  - SQL Over File Systems
    - Tutorial
    - Mappings
  - SQL Over JDBC
    - Mappings
  - SQL Over MongoDB
    - Mappings
  - Working with JSON
  - Stream Processing
  - Query Parameters
  - Finding Mappings
  - Improving Performance
  - Reflection Configuration
  - Troubleshooting
  - Statements
  - Functions and Expressions
  - SQL Data Types
  - User-Defined Types in SQL
  - Optimizing SQL queries
    - Partition Pruning
  - Predicates API
- Improving Query Performance
- Serialization
  - Overview
  - Compact Serialization
    - Compact Serialization Binary Specification
  - HazelcastJsonValue
  - Custom Serialization
  - Other Serialization Options
  - Configuring Serializers
- Listening to Events
- Transactions
  - Creating a Transaction Interface
  - Providing XA Transactions
- Testing Applications
- Troubleshooting
Operate & manage
- Configuration
  - Overview
  - Static Configuration
  - Dynamic Configuration
  - Phone Homes
- Configuring Logging
- Configuring the Jet Engine
- Maintaining a Cluster
- Partition Groups and Networking
- Securing a Cluster
  - Security Overview
  - TLS
  - Security Defaults
  - Enabling Security
  - Authentication
  - Client Authorization
  - Advanced Security Features
  - Security Hardening Recommendations
- Fault Tolerance
  - Backups
  - Persistence
  - Detecting Failures
  - Connection Timeouts
  - Fault Tolerance for Jobs
  - Handling Network Partitions
- CP Subsystem
- High-Density Memory Store
- Data Connections
  - Configuring Data Connections to External Systems
- Synchronizing Data Across Clusters
- Thread-Per-Core (TPC)
- Tiered Storage
- Extending Hazelcast
- OSGI
Integrate
- Overview
- Integrate with Spring
- Integrate with Feast
- Integrate with Vert.x
  - Get started with Vert.x
- Messaging System Connectors
- Database & CDC Connectors
- File Connectors
  - Unified File Connector
  - Legacy File Connector
- Hazelcast Data Structure Connectors
- Kafka Connect Source Connectors
- Socket Connectors
- Test Source Connectors
- Custom Connectors
- Community Connectors
Clients & APIs
Tools & plugins
Reference

Hazelcast Platform
Develop & build
Best practices

Best practices

6.0-SNAPSHOT 5.5 5.4 5.3 5.2 5.1 5.0

Learn more about best practices and Hazelcast recommendations:

Capacity Planning
Performance Tips
Back Pressure
Pipelining
AWS Deployments
Threading
Near Cache
IMap bulk read operations
Data Affinity

In-Memory Storage Capacity Planning

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