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ETL and Data Ingestion

ETL is an acronym for “extract, transform, load.” Extract refers to collecting data from some source. Transform refers to any processes performed on that data. Load refers to sending the processed data to a destination, such as a database. ETL is a data processing concept dating back to the 1970s, but it remains important today because it is one of the most dominant frameworks for providing people and applications with data. Engineering and product teams load and preprocess data from a variety of sources to a number of destinations with ETL techniques and software.

Real-Time Stream Processing

Hazelcast Jet provides all the necessary tools to build a real-time stream processing application. It is a powerful processing framework for querying data streams on top of an elastic in-memory storage system, where the process may ultimately store its results.

Redis Replacement

Redis is good for simple data caching use cases, but in the real world you will want more than simple caching from your in-memory computing platform. When you’ve hit a wall at scaling Redis or struggled to work around its security issues, it’s time to turn to Hazelcast.

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360° Customer View

The speed of in-memory solutions can drive your customer's experience to a new level of complete engagement through a fully-integrated perspective enabled by Machine Learning and powered by Artificial Intelligence.

Application Acceleration and Scaling

Hazelcast can be used to accelerate and scale your SaaS or custom internal applications by increasing throughput and reducing the latency of data accesses on disk-based databases. Add Hazelcast as an in-memory story between your application and your database to handle more users and higher load while improving response times. Updates that your applications make to data in Hazelcast will be passed through to the underlying database to ensure data synchronization.

Cache-as-a-Service (CaaS)

Hazelcast provides a cache-as-a-service for scalable, reliable, and fast caching. Applications can use Hazelcast as side-cache to their database, or place the database in-line behind the caching service.

Cache-as-a-Service (CaaS)

The cache is an important component of any application. In-memory caching can eliminate the bottlenecks of applications and provide predictable latency and fast response time to reach the growing mass of users. By implementing a Cache-as-a-Service across the organization, you can enable multiple applications to access managed in-memory cache rather than slow disk-based databases.

Caching

Operating in today’s always-on, high-volume, high-speed, high-expectation world requires a different level of processing enablement. When microseconds can mean the difference between success and failure, Hazelcast in-memory caching solutions can deliver blinding speed with scalable and flexible data caching.

Database Caching

Organizations rely on database caching to predictably scale mission-critical applications by providing in-memory access to frequently used data. As customer data grows exponentially, organizations of all sizes are turning to in-memory solutions to scale applications to meet service level agreements, offload over-burdened shared data services, and provide availability guarantees.

Digital Transformation

Digital transformation touches every part of the modern business. In-memory technology is one of the core enablers in today's data-intensive, always-on world. If speed, scalability, and stability are critical to your business, Hazelcast is the answer.

ETL and Data Ingestion

ETL is an acronym for “extract, transform, load.” Extract refers to collecting data from some source. Transform refers to any processes performed on that data. Load refers to sending the processed data to a destination, such as a database. ETL is a data processing concept dating back to the 1970s, but it remains important today because it is one of the most dominant frameworks for providing people and applications with data. Engineering and product teams load and preprocess data from a variety of sources to a number of destinations with ETL techniques and software.

Fast Batch Processing

Hazelcast Jet employs many performance optimizations to speed up batch processing up to 15 times compared to Spark or Flink. Hadoop is overperformed by magnitudes.