This short video explains why companies use Hazelcast for business-critical applications based on ultra-fast in-memory and/or stream processing technologies.
Stream processing is a hot topic right now, especially for any organization looking to provide insights faster. But what does it mean for users of Java applications, microservices, and in-memory computing?
In this webinar, we will cover the evolution of stream processing and in-memory related to big data technologies and why it is the logical next step for in-memory processing projects.
Now, deploying Hazelcast-powered applications in a cloud-native way becomes even easier with the introduction of Hazelcast Cloud Enterprise, a fully-managed service built on the Enterprise edition of Hazelcast IMDG. Can't attend the live times? You should still register! We'll be sending out the recording after the webinar to all registrants.
Most web applications often persist data from one request to the next. Web applications are dynamic, making calculations and database queries to serve requests. This overhead can be expensive, especially when we need the same data repeatedly. Django-based applications are no exception to this challenge. Ideally, we’d like a place to persist data between requests […]
The Hazelcast Python Client lets developers connect to Hazelcast clusters from Python apps and services. We can use the client to handle all of Hazelcast’s distributed data structures. We can also subscribe to cluster and data structure events. In this tutorial, we’ll explore how to install the client and use some of its key features. […]
Generating content served from an ASP.NET application can be slow and expensive — particularly when there’s heavy use of database calls. Relational databases are historically challenging to scale. Implementing caching means that the application doesn’t have to fetch and process the same data again and again. It’s one of the most effective ways to improve […]
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We can send an SQL query to Hazelcast and get results, a great feature. But did you know the data doesn’t have to be stored in Hazelcast to be queryable via Hazelcast? It could be somewhere like a Kafka topic or a CSV file, and you can still query it using Hazelcast’s SQL. This makes […]
Many organizations today are looking to gain real-time responsiveness from their IT infrastructure, if not for gaining competitive advantage, then for not getting left behind. It’s not always obvious when your business is doing “well enough,” as you might have consistently positive engagements with your customers, but at the same time, are you doing as […]
We are proud to announce the first beta release of Hazelcast Platform 5.0. Attentive readers might notice the name of the release is just “Hazelcast Platform”, and not “Hazelcast IMDG” or “Hazelcast Jet”. In this blog post, we’ll explain the changes in the product name and how it relates to the IMDG and Jet products. […]
This week we’re launching a new web series we’re calling HazelVision. HazelVision is a set of technically oriented videos geared toward topics of interest to a technical audience. We’ll try to keep them to around 5 minutes each so they’re quick to watch, but we’ll point you to sources of deeper information if you want […]
We have released the Python client 4.2, featuring the brand new SQL support! You can start using it to query your data efficiently with the widely-known standard SQL syntax. You can install the latest version through PyPI by issuing the following command. pip install -U hazelcast-python-client SQL Support For a long time, Hazelcast IMDG and […]
Hazelcast Node.js Client 4.2 is now available! In this post, you can find information on the main updates, including the brand-new SQL querying feature. SQL Support Node.js client now supports querying against the new, state-of-the-art SQL engine introduced in Hazelcast IMDG 4.1. With the new engine: You can query with many new SQL expressions. You […]
Two years ago, when Forrester last published its Wave for Streaming Analytics, our streaming capabilities were still in the R&D phase. We were working on a technological challenge based on the belief there was a new generation of stream processing that was possible – one steeped in our ethos of defeating time. For the world […]
One of the features of Hazelcast Enterprise is the ability to share data between multiple Hazelcast clusters, whether geographically distant or adjacent. In this blog, we’ll look at the practicalities of keeping the data in multiple clusters synchronized. Business continuity wins There are two conflicting needs here. Data replication happens fastest the nearer the clusters […]
“Which serialization option is best?“. In this post we’ll explore some of the most common serialization options for Hazelcast, which includes standard coding, and the external libraries Avro, Kryo and Protobuf. Following our previous posts on how much memory you will need (here and here) which looked at object sizing in Java, we need to […]
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