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8 Data Ingestion Tools (Quick Reference Guide)

Monte Carlo

At the heart of every data-driven decision is a deceptively simple question: How do you get the right data to the right place at the right time? The growing field of data ingestion tools offers a range of answers, each with implications to ponder. Fivetran Image courtesy of Fivetran.

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Stream Rows and Kafka Topics Directly into Snowflake with Snowpipe Streaming

Snowflake

This solution is both scalable and reliable, as we have been able to effortlessly ingest upwards of 1GB/s throughput.” Rather than streaming data from source into cloud object stores then copying it to Snowflake, data is ingested directly into a Snowflake table to reduce architectural complexity and reduce end-to-end latency.

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How-to: Index Data from S3 via NiFi Using CDP Data Hubs

Cloudera

The scenario is the same as it was in the previous blog but the ingest pipeline differs. Spark as the ingest pipeline tool for Search (i.e. Provide a collection Name under Destination (in this example, we named it ‘solr-nifi-demo’). nifi-solr-demo. nifi-solr-demo. solr-nifi-demo-collection. text_general.

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Top Data Lake Vendors (Quick Reference Guide)

Monte Carlo

We continuously hear data professionals describe the advantage of the Snowflake platform as “it just works.” Snowpipe and other features makes Snowflake’s inclusion in this top data lake vendors list a no-brainer. It’s frustrating…[Lake Formation] is a step-level change for how easy it is to set up data lakes,” he said.

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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers.

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A Breakthrough Architecture for Real-Time Analytics- An Overview of Compute-Compute Separation in Rockset

Rockset

Developers can spin up or down virtual instances based on the performance requirements of their streaming ingest or query workloads. In addition, Rockset provides fast data access through the use of more performant hot storage, while cloud storage is used for durability.

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The Good and the Bad of Databricks Lakehouse Platform

AltexSoft

Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. Besides that, it’s fully compatible with various data ingestion and ETL tools. Let’s see what exactly Databricks has to offer.

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