Marin Engineering
Marin Software's Tech Blog

Optimizing Apache Phoenix Query Patterns For Low Latency Applications FR

FR – At Marin, we have a number of customer-facing and near-real-time applications that demand lightning fast response times from our data storage systems, including Apache Phoenix. By and large, we here at Marin are very happy with Phoenix and its performance, but some tweaking was still necessary to achieve the necessary latency. While many […]

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Optimizing Apache Phoenix Query Patterns For Low Latency Applications

At Marin, we have a number of customer-facing and near-real-time applications that demand lightning fast response times from our data storage systems, including Apache Phoenix. By and large, we here at Marin are very happy with Phoenix and its performance, but some tweaking was still necessary to achieve the necessary latency. While many of these […]

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The hype behind using frameworks like Spark is simple – handle ever increasing amounts of data without code changes. A megabyte should be processed with the same ease as a terabyte. And configuration changes needed, if any, should be minimal. Of course, in order to process voluminous data with speed, the distributed computing framework will […]

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unemerging

At Marin, we build a product to help our customers analyze and redistribute their advertising budget to get the maximum return on investment. Sounds simple. But how do you do that for a customer with one million ads? Ten million ads? Within an acceptable time frame? Our answer – our distributed data ingestion and query […]

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Digital Advertising Storage on Apache HBase and Apache Phoenix

In this post, we examine a data platform that uses Apache Phoenix over Apache HBase as a persistent storage for objects used in managing digital advertising campaigns. Background At Marin, we support cross-channel ad management for search, social, display and shopping. Our initial architecture stored our data silos – in MySQL shards or MongoDB shards […]

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