30. 01. 2023.

Real-time Deep Learning at Bug Future Show conference

On Thursday, February 2, 2023, the tenth Bug Future Show will be held, which for the first time will introduce a third parallel track called “.debug Future Show” intended primarily for IT people, where, among other things, you can find my lecture titled called “Real-time Deep Learning” starting at 11:15.   This is a short […]

19. 11. 2022.

ISAQB Software Architecture Gathering post conference impressions

From November 14 – 17 2022 I attended the Software Architecture Gathering for the first time. Here are my post conference impressions. Unlike majority of IT conferences which serves more or less as a marketing field to propagate interests of big software and Cloud companies behind the conference, this one is an exception, although even […]

19. 06. 2022.

How to speedup pooling queries from the Oracle database

This post is a kind of extension of my previous post named “How to index only rows of interest” which can be found on the following link: https://www.josip-pojatina.com/en/how-to-index-only-rows-of-interest/   Having issues with pooling queries are very common in old, SOA based architectural style, where ESB (Enterprise Service Bus) are throwing the same query again and […]

30. 05. 2022.

How to get 100% cache hit rate by using Change Data Capture & Redis

In this blog I’ll explain how to get 100% cache hit rate by using CDC (Change Data Capture) technology and Redis cache.   There are multiple benefits of having caching layer in front of back-end database system. By fetching data from the cache instead of back-end we are actually free up valuable database resources for […]

25. 02. 2022.

Redis performance tuning – Top 10 mistakes

Redis is the most popular Key-value data store and one of the most popular database systems overall.   According to Db-engine ranking: https://db-engines.com/en/ranking/key-value+store (You can check the picture below), Redis is on the top position by large margin among Key-values data stores. Amazon DynamoDb on the second place, lags behind Redis more than a twice. […]

26. 01. 2022.

StreamSets review – creating real time data pipelines in no time

In this post I’ll try to review StreamSets Data Collector, one of the most popular tools for creating smart data pipelines for streaming, batch and change data capture, which allows you to move data around in a near real time.   First I’d like to point out that the whole review is my own personal […]

29. 12. 2021.

Apache Ignite – distributed In-memory SQL database

Apache Ignite is one of the very few In-memory SQL compliant distributed databases/data grid among open-source projects. It’s often called “Redis done right” or “Redis on steroid”, because Redis looks primitive and limited when compared with Apache Ignite. Ignite offers great flexibility and lot of features that can easily fit to many use cases. Instead […]

23. 12. 2021.

YugabyteDb – distributed SQL database for a new age

Recently I’ve got a chance to try YugabyteDb, one of the new age databases which try to tackle with new requirements such as scalability, resilience, high availability, Cloud/Hybrid readiness and new architecture styles based on microservices. Although Yugabyte is relatively young company, it attracts a lot of attention, not only from architects/developers/admins, but also from […]

06. 12. 2021.

How to create a real time machine learning pipeline with StreamSets Transformer

Artificial Intelligence (AI) with its subset ML (Machine learning) is probably one of the hottest topics in IT industry today. Many companies are struggling to implement AI algorithms into data pipelines to make smarter decisions with more or less success. First of all, the AI is a wide topics which requires knowledge of math, statistics, […]

29. 11. 2021.

Complex near real-time transformations in data pipelines

For many years, ETL daily batch job was the dominant way to perform data transformations before loading in Data Warehouse. These days requirements are quite different starting with the most important one which is to ensure that new data has to be available for AI/ML and analysis near real time. Moreover, classical DWH databases are […]