Aggregated Data Data Ingestion Data Lake 
DareData
JULY 5, 2023
Learn how we build data lake infrastructures and help organizations all around the world achieving their data goals. In today's data-driven world, organizations are faced with the challenge of managing and processing large volumes of data efficiently.
DareData
JANUARY 30, 2023
Our goal is to help data scientists better manage their models deployments or work more effectively with their data engineering counterparts, ensuring their models are deployed and maintained in a robust and reliable way. DigDag: An open-source orchestrator for data engineering workflows. Stanford's Relational Databases and SQL.
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Striim
OCTOBER 11, 2024
Self-Service Management Modern data pipelines facilitate seamless integration between a wide range of tools, including data integration platforms, data warehouses, data lakes, and programming languages. Plus, our platform features scalable in-memory streaming SQL for real-time data processing and analysis.
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 .
WeCloudData
OCTOBER 19, 2021
Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.
WeCloudData
OCTOBER 19, 2021
Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.
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. The majority are still draining streaming data into a data lake or a warehouse and are doing batch analytics.
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