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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022. Logs on Grail Log data is foundational for any IT analytics.

Analytics 186
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Conducting log analysis with an observability platform and full data context

Dynatrace

Causal AI—which brings AI-enabled actionable insights to IT operations—and a data lakehouse, such as Dynatrace Grail , can help break down silos among ITOps, DevSecOps, site reliability engineering, and business analytics teams. “The weakness of a data lake is they fail when you need to access them fast,” Pawlowski said.

Analytics 187
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Bulldozer: Batch Data Moving from Data Warehouse to Online Key-Value Stores

The Netflix TechBlog

Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy. How Bulldozer leverages Spark, Protobuf and KV DAL for moving the data.

Latency 243
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Music to my Ears - All Things Distributed

All Things Distributed

We see that with our Amazon customers; when they hear a great tune on a radio they may identify it using the Shazam or Soundhound apps on their mobile phone and buy that song instantly from the Amazon MP3 store. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. At werner.ly Syndication.

AWS 138
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Should You Use ClickHouse as a Main Operational Database?

Percona

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. This information can be a mix of analytical (OLAP) queries (i.e. Analytical databases are optimized for a low number of slow queries.