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Combating financial fraud and money laundering at scale with Apache Druid
Learn how Apache Druid enables financial services firms and FinTech companies to get immediate insights from petabytes-plus data volumes for anti-fraud and anti-money laundering compliance.
Imply Pivot delivers the final mile for modern analytics applications
This blog is focused on how Imply Pivot delivers the final mile for building an anlaytics app. It showcases two customer examples - Twitch and ironsource.
Why Open Source Matters for Databases
Apache Druid is at the heart of Imply. We’re an open source business, and that’s why we’re committed to making Druid the best open source database for modern analytics applications
Ingestion from Confluent Cloud and Kafka in Polaris
How to ingest data into Imply Polaris from Confluent Cloud and from Apache Kafka
What Makes a Database Built for Streaming Data?
For an analytics app to handle real-time, streaming sources, it must be built for streaming data. Druid has 3 essential features for stream data.
SQL-based Transformations and JSON Columns in Imply Polaris
You can easily do data transformations and manage JSON data with Imply Polaris, both using SQL.
Approximate Distinct Counts in Imply Polaris
When it comes to modern data analytics applications, speed is of the utmost importance. In this blog we discuss two approximation algorithms which can be used to greatly enhance speed with only a slight reduction in accuracy. We further explain how to use these algorithms in Imply Polaris - Imply’s SaaS Platform
The next chapter for Imply Polaris: celebrating 250+ accounts, continued innovation