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@@ -338,6 +338,7 @@ You can read more about this distinction on Prof. Daniel Abadi's blog: [Distingu
* [Facebook PrestoDB](https://prestodb.io/) - distributed SQL query engine.
* [Google BigQuery](https://research.google.com/pubs/pub36632.html) - framework for interactive analysis, implementation of Dremel.
* [Materialize](https://github.com/materializeinc/materialize) - is a streaming database for real-time applications using SQL for queries and supporting a large fraction of PostgreSQL.
* [Invantive SQL](https://documentation.invantive.com/2017R2/invantive-sql-grammar/invantive-sql-grammar-17.30.html) - SQL engine for online and on-premise use with integrated local data replication and 70+ connectors.
* [PipelineDB](https://www.pipelinedb.com/) - an open-source relational database that runs SQL queries continuously on streams, incrementally storing results in tables.
* [Pivotal HDB](https://pivotal.io/pivotal-hdb) - SQL-like data warehouse system for Hadoop.
* [RainstorDB](http://rainstor.com/products/rainstor-database/) - database for storing petabyte-scale volumes of structured and semi-structured data.
@@ -405,6 +406,7 @@ You can read more about this distinction on Prof. Daniel Abadi's blog: [Distingu
* [Apache Oozie](http://oozie.apache.org/) - workflow job scheduler.
* [Azure Data Factory](https://docs.microsoft.com/en-us/azure/data-factory/data-factory-introduction) - cloud-based pipeline orchestration for on-prem, cloud and HDInsight
* [Chronos](http://mesos.github.io/chronos/) - distributed and fault-tolerant scheduler.
* [Dagster](https://github.com/dagster-io/dagster) - a data orchestrator for machine learning, analytics, and ETL.
* [Linkedin Azkaban](https://azkaban.github.io/) - batch workflow job scheduler.
* [Schedoscope](https://github.com/ottogroup/schedoscope) - Scala DSL for agile scheduling of Hadoop jobs.
* [Sparrow](https://github.com/radlab/sparrow) - scheduling platform.
@@ -738,6 +740,8 @@ for Data Analytics at Twitter.
* [Spark in Motion](https://www.manning.com/livevideo/spark-in-motion) - Spark in Motion teaches you how to use Spark for batch and streaming data analytics.
* [Machine Learning, Data Science and Deep Learning with Python ](https://www.manning.com/livevideo/machine-learning-data-science-and-deep-learning-with-python) - LiveVideo tutorial that covers machine learning, Tensorflow, artificial intelligence, and neural networks.
* [Data warehouse schema design - dimensional modeling and star schema](https://snir.dev/talks/data-warehouse-schema-design) - Introduction to schema design for data warehouse using the star schema method.
* [Elasticsearch 7 and Elastic Stack](https://www.manning.com/livevideo/elasticsearch-7-and-elastic-stack) - LiveVideo tutorial that covers searching, analyzing, and visualizing big data on a cluster with Elasticsearch, Logstash, Beats, Kibana, and more.
## Books