Aggregated Data Data Ingestion Kafka 
Confluent
FEBRUARY 6, 2019
The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. For now, we’ll focus on Kafka.
Lyft Engineering
NOVEMBER 29, 2023
Druid at Lyft Apache Druid is an in-memory, columnar, distributed, open-source data store designed for sub-second queries on real-time and historical data. Druid enables low latency (real-time) data ingestion, flexible data exploration and fast data aggregation resulting in sub-second query latencies.
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Cloudera
FEBRUARY 16, 2021
In the following sections, we see how the Cloudera Operational Database is integrated with other services within CDP that provide unified governance and security, data ingest capabilities, and expand compatibility with Cloudera Runtime components to cater to your specific use cases. . Integrated across the Enterprise Data Lifecycle .
Striim
JULY 31, 2024
Why Striim Stands Out As detailed in the GigaOm Radar Report, Striim’s unified data integration and streaming service platform excels due to its distributed, in-memory architecture that extensively utilizes SQL for essential operations such as transforming, filtering, enriching, and aggregating data.
Rockset
APRIL 18, 2023
Under the hood, Rockset utilizes its Converged Index technology, which is optimized for metadata filtering, vector search and keyword search, supporting sub-second search, aggregations and joins at scale. Feature Generation: Transform and aggregate data during the ingest process to generate complex features and reduce data storage volumes.
Rockset
AUGUST 30, 2021
Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. But until this release, all these data sources involved indexing the incoming raw data on a record by record basis.
Rockset
OCTOBER 4, 2022
Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Event streams, such as clickstreams, IoT data and other time series data, are common sources of data into these apps. The broad adoption of Apache Kafka has helped make these event streams more accessible.
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