Analytics Application Blog Data Ingestion 
Rockset
MAY 12, 2022
We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them! Lambda systems try to accommodate the needs of both big data-focused data scientists as well as streaming-focused developers by separating data ingestion into two layers.
Rockset
MAY 3, 2023
lower latency than Elasticsearch for streaming data ingestion. In this blog, we’ll walk through the benchmark framework, configuration and results. We’ll also delve under the hood of the two databases to better understand why their performance differs when it comes to search and analytics on high-velocity data streams.
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Cloudera
AUGUST 13, 2021
The ability to manage how the data flows and transforms during the first mile of the data pipeline and control the data distribution can accelerate the performance of all analytic applications. By modernizing the data flow, the enterprise got better insights into the business.
Cloudera
MAY 30, 2024
By leveraging the flexibility of a data lake and the structured querying capabilities of a data warehouse, an open data lakehouse accommodates raw and processed data of various types, formats, and velocities. Learn more about the Cloudera Open Data Lakehouse here.
Rockset
JANUARY 30, 2024
Microbatching : An option to microbatch ingestion based on the latency requirements of the use case. In this blog, we delve into each of these features and how they are giving users more cost controls for their search and AI applications. Microbatching Rockset is known for its low-latency streaming data ingestion and indexing.
Cloudera
JUNE 16, 2022
CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report. Faster data ingestion: streaming ingestion pipelines. In subsequent blogs, we’ll deep dive into use cases across a number of verticals and discuss how they were implemented using CSP. Conclusion. Not to worry.
Cloudera
FEBRUARY 9, 2021
Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.
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