Welcome to" Popular Data Warehouse Systems." After watching this video, you will be able
to: Categorize popular data warehouse systems. List some of the more popular data warehouse
vendors and their warehousing offerings. Most data warehouse systems are supported
via one or more of three platforms. First are appliances, which are pre-integrated
bundles of hardware and software that provide high performance for workloads and low maintenance
overhead. Other vendors support cloud deployments only,
offering the benefits of cloud scalability and pay-per-use economics, and in many cases,
deliver their data warehouses as fully managed services. Some warehouse offerings have traditionally
been available as software installed only within on-premises environments, but in recent
years, most of these vendors now offer cloud-deployed data warehouse systems. Let's view an unranked list of popular data
warehouse systems and learn more about them. Let's begin with appliance data warehouse
system solutions, such as Oracle Exadata. An organization can deploy this data warehouse
solution as part of an on-premises installation or via Oracle Public Cloud. Oracle Exadata features built-in algorithms
and runs all types of workloads, including OLTP, data warehouse analytics, in-memory
analytics, and mixed workloads. IBM Netezza is another warehousing appliance. ​ You can deploy IBM Netezza on IBM Cloud, Amazon
Web Services, Microsoft Azure,​ and private clouds using the IBM Cloud Pak for Data System. ​ IBM Netezza is widely recognized for its data
science and machine-learning enablement.​ Next, let's turn our attention to some of
the more recognized cloud-based data warehouse systems providers.​ Amazon RedShift uses Amazon Web Services-specific
hardware and proprietary software in the cloud for accelerated data compression and encryption,
machine learning, and graph-optimization algorithms that automatically organize and store data. Up-and-coming Snowflake offers a multi-cloud
analytics solution that complies with GDPR and CCPA data privacy regulations. Snowflake advertises its always-on encryption
of data in transit and at rest. Snowflake is FedRAMP Moderate authorized. Next, Google BigQuery describes its data warehouse
system as a "flexible, multi-cloud data warehouse solution." Google reports data warehouse uptime of 99.99%
and delivery of sub-second query response times from any business intelligence tool.
Google BigQuery's system specifies petabyte speed and massive concurrency to deliver real-time
analytics. Now let's check out the vendors that provide
both on-premises and cloud-based data warehouse systems. Microsoft Azure Synapse Analytics offers code-free
visual ETL/ELT processes to ingest data from more than 95 native connectors. Azure Synapse Analytics supports data lake
and data warehouse use cases and supports the use of T-SQL, Python, Scala, Spark SQL,
and dot Net for both serverless and dedicated resources. Teradata Vantage takes a slightly different
approach. Teradata Vantage advertises its multi-cloud
data platform for enterprise analytics that unifies data lakes, data warehouses, analytics,
and new data sources and types. Teradata Vantage combines open source and
commercial technologies to operationalize insights and delivers performance for mixed
workloads with high query concurrency using workload management and adaptive optimization. For support, Teradata provides a single point
of contact for operational task services including monitoring, change requests, performance tuning,
security management, and reporting. IBM Db2 Warehouse is widely recognized for
its scalability, massively parallel processing capabilities, petaflop speeds, security features,
and 99.99% service uptime. IBM Db2 Warehouse provides a containerized
scale-out data warehousing solution. You can move workloads where needed, including the
public cloud, private cloud, or on-premises--with minimal or no changes required. Vertica, another known hybrid-cloud data warehouse
system, provides multi-cloud support for Amazon Web Services, Google, Microsoft Azure, and
on-premises Linux hardware. Vertica reports fast multi-GB data transfer
rates, scalable, elastic compute and storage, and notable system fault tolerance when using
Eon mode. Oracle Autonomous Data Warehouse runs in Oracle
Public Cloud and on-premises with support for multi-model data and multiple workloads. Oracle describes its system as built to eliminate
manual data management and reports that they provide extensive automated security features,
including autonomous data encryption both at rest and in motion, protection of regulated
data, security patch application, and threat detection. In this video, you learned that: Data warehouse systems can include appliances,
exist on-premises, exist in the cloud, or use a combination of these deployment options. Popular data warehouse vendors include Oracle,
Teradata, Vertica, Google, IBM, Microsoft, Snowflake, Amazon, and others.