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Why Hazelcast

Hazelcast provides the leading in-memory computing platform for high-performance data processing at scale, accelerating applications for the most innovative global brands.


The world in which businesses and their information systems operate has completely changed. Billions of devices stream terabytes of data continuously; this information needs to be ingested, contextualized, processed, and published – millions of times per second. This is the new normal.

Hazelcast in-memory solutions deliver unprecedented speed, scalability, stability, and enterprise-grade security for your most important applications. The world’s most demanding companies rely on us to accelerate their mission-critical applications because we offer the most effective and efficient solutions to address the needs of the digital world.

Go faster with leading products, services, and deployability

The Leading In-Memory Computing Platform

The Leading In-Memory Computing Platform

Architected for environments that require extremely high throughput, low latency, horizontal scaling, and security, Hazelcast accelerates applications by letting you use the power of in-memory computing. The Hazelcast In-Memory Computing Platform is comprised of Hazelcast IMDG, the most widely deployed in-memory data grid, and Hazelcast Jet, the industry’s most advanced in-memory stream processing solution.

Support Services

Support Services

Hazelcast offers expert help in delivering in-memory solutions, resulting in lower risk, shortest time-to-value, and the quickest path to self-sufficiency. With the primary objectives being the empowerment of our clients and their preferred implementation partners, our certified staff brings best practices based on our experience working with the world’s largest companies to train and support their staff during the deployment, upgrade and integration phases of their applications’ lifecycles.

Deploy Anywhere

Deploy Anywhere

The cloud-native Hazelcast architecture is available for multiple cloud platforms and on-premises deployments. Register for Hazelcast Cloud Enterprise to get the elasticity and production-ready benefits of a managed service on AWS, Azure, and GCP. Or download the software and embed Hazelcast into your applications to get the acceleration of distributed, in-memory processing in your cluster.

Why choose an in-memory computing platform?

An in-memory computing platform offers many advantages over other popular technologies today. See how Hazelcast compares below to other in-memory technologies like in-memory databases, big data platforms, and NoSQL databases.

Capability Other In-Memory Data Offerings Big Data Platforms NoSQL Offerings
Distributed Data
  • Fastest, lowest, latency
  • Data-aware
  • Scalable and elastic
  • Less scalable
  • Less elastic
  • clustering often limited
  • Disk-based
  • Not low-latency
  • Complex to manage
  • Disk-based
  • Not low-latency
Distributed Compute
  • Fastest, lowest, latency
  • Data-aware
  • Multi-language
  • Elastic, embeddable
  • APIs often limited
  • Many not elastic
  • Not embeddable or not cloud-native
  • Not real-time or low-latency
  • Designed for batch, fast-batch and ETL
  • Relies on other platform (BigData, Data Grid, or Stream Processing)
Stream Processing
  • Low-latency, data locality
  • Elastic & resilient
  • Advanced stream logic
  • Lightweight, embeddable
  • Reliable job management
  • Many rely on BigData
  • Others lack:
    • Advance logic
    • Elastic jobs
    • Reliable/resilient jobs
  • Disk-based-persistence
  • Lacks data grid
  • Not low-latency
  • Complex to manage
  • Relies on other platform (BigData, Data Grid, or Stream Processing)
Ingest & ETL
  • Distributed ingest via Jet
  • Embeddable
  • Fast & low latency
  • Lack streaming engine
  • Not optimized for real-time
  • Not low-latency
  • Complex to manage
  • Designed for batch
  • Rely on partner technologies for Ingest such as Kafka & Spark
Cloud, Fog & IoT Ready
  • Elastic, cloud-native
  • Embeddable, Edge/Fog
  • microservices, serverless
  • Many aren’t embeddable
  • Clustering often master/slave
  • Not truly cloud-native
  • Not embedable
  • Unsuitable for Edge/Fog
  • Not truly cloud-native
  • Not embeddable
  • Unsuitable for Edge/Fog
Clients & Languages
  • Advanced APIs
  • Embeddable & lightweight
  • Often limited in data structures
  • Many languages, but they require extra frameworks
  • Lack distributed compute, ingest and streaming APIs

Performance Benchmarks

See how we compare to other technologies

Let's Get Started!

Contact us now to learn more about how our in-memory computing platform can help you leverage data in ways that immediately produce insight and actions.