Apr 20, 2022
Dear Community,
Many thanks for yor support and help!
Teradata and Apache Hadoop are key players in the realm of data management solutions. Teradata stands out with its strong performance and advanced analytics, while Apache Hadoop offers a cost-effective, open-source option suitable for varied data. Teradata may have the upper hand for enterprises requiring high performance and scalability for complex queries.
Features: Teradata is renowned for its massive parallel processing, shared-nothing architecture, and a host of advanced analytics capabilities, offering robust performance and scalability. Conversely, Apache Hadoop excels with its HDFS and Spark framework, ensuring seamless integration of tools and cost-efficient large-scale data storage. Its adaptability to handle varied data types makes it appealing to businesses.
Room for Improvement: Teradata's high costs, complex interface, and limited cloud adoption are prominent concerns. Users frequently request better support for unstructured data and enhanced analytics. Apache Hadoop faces criticism for its setup complexity, limited user-friendliness, and often slower support infrastructure, with users calling for better integration and real-time processing improvements.
Ease of Deployment and Customer Service: Teradata supports on-premise, cloud, and hybrid deployment; however, initial setup is often seen as complicated, with technical support receiving varied feedback. Apache Hadoop's deployment, which includes on-premises and cloud, can challenge newcomers, while its support offers average response times with room for improvement.
Pricing and ROI: Teradata, though known for its substantial upfront costs, promises solid ROI for large-scale operations and has recently worked towards flexible pricing models. Apache Hadoop's main advantage is its open-source nature, offering affordability for large-scale data operations, though some advanced features may incur extra fees, leading to potential cost considerations.
It's not structured support, which is why we don't use purely open-source projects without additional structured support.
The technical support from Teradata is quite advanced.
Customer support is very good, rated eight out of ten under our essential agreement.
It is a distributed file system and scales reasonably well as long as it is given sufficient resources.
This expansion can occur without incurring downtime or taking systems offline.
Scalability is complex as you need to purchase a license and coordinate with Teradata for additional disk space and CPU.
Continuous management in the way of upgrades and technical management is necessary to ensure that it remains effective.
I find the stability to be almost a ten out of ten.
The workload management and software maturity provide a reliable system.
The problem with Apache Hadoop arose when the guys that originally set it up left the firm, and the group that later owned it didn't have enough technical resources to properly maintain it.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.
Teradata is much more expensive than SQL, which is well-performed and cheaper.
If you don't do the upgrades, the platform ages out, and that's what happened to the Hadoop content.
The data mover is valuable over the last two years as it allows us to achieve data replication to our disaster recovery systems.
Teradata is a scalable data analytics platform designed to meet enterprise demands for large-scale data management and processing, focusing on performance, scalability, and security for complex query executions.
As a leading data warehousing solution, Teradata integrates advanced analytics enabling organizations to derive insights from massive datasets. It supports high-volume data workloads with its architecture optimized for analytical queries. Users benefit from its robust scalability, allowing seamless expansion as data grows. Teradata's SQL engine is compatible with a wide range of data types, ensuring flexibility in data analysis. With advanced security measures, it protects sensitive data across various environments, providing peace of mind to users handling critical information.
What are the most important features of Teradata?Teradata is widely used in industries like finance, telecommunications, and healthcare, where data-driven decisions are critical. Companies leverage its robust analytics capabilities to enhance customer experiences, streamline operations, and ensure compliance with regulatory requirements. In these sectors, quick access to data insights can significantly impact competitive advantage.
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