Apr 20, 2022
Dear Community,
Many thanks for yor support and help!
Teradata and Apache Hadoop compete in the big data analytics category. Teradata appears to have the upper hand due to its performance and reliability in handling complex queries and advanced analytics.
Features: Teradata provides robust massively parallel processing, a shared-nothing architecture for exceptional speed, and excellent data warehousing capabilities. Its advanced analytics and reliable workload management are also noteworthy. Apache Hadoop is valued for handling large volumes of unstructured data efficiently, offering open-source scalability and cost-effectiveness, and providing parallel processing that integrates flexibly with various analytics tools.
Room for Improvement: Teradata faces challenges with cost, scalability, and cloud integration, with users seeking better solutions for unstructured data and improved interfaces. Apache Hadoop struggles with real-time data processing and user friendliness, with users looking for streamlined integration and advanced analytics capabilities.
Ease of Deployment and Customer Service: Teradata offers deployment flexibility across on-premises, cloud, and hybrid environments, though setup can be complex. Its customer service is highly rated for professional assistance and training. Apache Hadoop offers versatility in deployment, primarily on-premises and cloud, but lacks an integrated support structure, leading to desires for more cohesive support and simplified deployment.
Pricing and ROI: Teradata is expensive but offers significant ROI in large-scale implementations due to its performance and comprehensive support. Smaller enterprises might find the pricing a barrier. Apache Hadoop's open-source nature makes it cost-effective for scalable data needs, though enterprise-level support and deployment can increase costs. Users appreciate its affordability for big data solutions despite potential added expenses for features and support.
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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