Apr 20, 2022
Dear Community,
Many thanks for yor support and help!
Teradata and Apache Hadoop are prominent competitors in the data management and analytics sector. Teradata appears to have the upper hand for structured data management and speed, while Hadoop offers flexibility and cost-effectiveness, especially for unstructured data.
Features: Teradata supports massive parallel processing, scalability, and advanced analytics, making it efficient for complex query execution. Key features such as Teradata Performance Optimization and QueryGrid enhance data management. Apache Hadoop is valued for its distributed file system, handling vast data types, and facilitating large data processing through MPP architecture. It offers flexibility in data storage and significant cost advantages.
Room for Improvement: Teradata users seek enhancements in cloud offerings, user interface, and cost structure. It could improve on-premises scaling and unstructured data handling. Apache Hadoop needs advancements in user-friendliness and easing its steep learning curve. Real-time processing capabilities and stronger community support are areas for improvement.
Ease of Deployment and Customer Service: Teradata provides options for on-premises, hybrid, and public cloud deployments, though on-premises setup can be complex. Technical support is generally strong but sometimes slow. Apache Hadoop offers on-premises and cloud deployment, benefits from open-source community support, but lacks formal support unless through commercial distributions. Teradata's customer service is regarded as more robust.
Pricing and ROI: Teradata's pricing structure is premium, reflecting its capabilities, with notable ROI through analytics and staffing efficiency. Pricing negotiations are recommended due to high initial costs. Apache Hadoop is a cost-effective open-source solution, appealing to companies with budget constraints. It yields ROI through efficient large data set handling, despite some commercial support costs.
At least fifteen to twenty percent of our time has been saved using Teradata, which has positively affected team productivity and business outcomes.
Independent research showed that Teradata VantageCloud users achieved an average ROI of 427% across three years with payback under a year, demonstrating the platform's ability to deliver a strong financial return.
We have realized a return on investment, with a reduction of staff from 27 to eight, and our current return on investment is approximately 14%.
It's not structured support, which is why we don't use purely open-source projects without additional structured support.
The customer support for Teradata has been great.
They are responsive and knowledgeable, and the documentation is very helpful.
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.
Whenever we need more resources, we can add that in Teradata, and when not needed, we can scale it down as well.
This flexibility allows organizations to scale according to their needs, balancing performance, cost, and compliance requirements.
This expansion can occur without incurring downtime or taking systems offline.
Continuous management in the way of upgrades and technical management is necessary to ensure that it remains effective.
Its massively parallel process architecture allows the platform to distribute workload efficiently, enabling organizations to run heavy analytic queries without compromising speed or stability.
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.
I want to highlight two features for improvement: first, storing data in various formats without requiring a tabular structure, accommodating unstructured data; and second, adding AI ML features to better integrate Gen AI, LLM concepts, and user-friendly experiences such as text-to-SQL capabilities.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
The most challenging aspect is finding Teradata resources, so we are focusing on internal training and looking for more Teradata experts.
Teradata is much more expensive than SQL, which is well-performed and cheaper.
Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.
Role-based access control (RBAC), strong audit and compliance features, high availability, fault tolerance, and encrypted data at rest and in-transit are key features.
If you don't do the upgrades, the platform ages out, and that's what happened to the Hadoop content.
I assess Apache Hadoop's fault tolerance during hardware failures positively since we have hardware failover, which works without problems.
Teradata's security helps our organization meet compliance requirements such as GDPR and IFRS, and it is particularly essential for revenue contracting or revenue recognition.
Its architecture allows information to be processed efficiently while maintaining stable performance, even in highly demanding environments.
It facilitates data integration, where we integrate and analyze data from various sources, making it a powerful and high-quality reliable solution for the company.
| Product | Market Share (%) |
|---|---|
| Teradata | 9.5% |
| Apache Hadoop | 3.5% |
| Other | 87.0% |
| Company Size | Count |
|---|---|
| Small Business | 14 |
| Midsize Enterprise | 8 |
| Large Enterprise | 21 |
| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 13 |
| Large Enterprise | 52 |
Teradata is a powerful tool for handling substantial data volumes with its parallel processing architecture, supporting both cloud and on-premise environments efficiently. It offers impressive capabilities for fast query processing, data integration, and real-time reporting, making it suitable for diverse industrial applications.
Known for its robust parallel processing capabilities, Teradata effectively manages large datasets and provides adaptable deployment across cloud and on-premise setups. It enhances performance and scalability with features like advanced query tuning, workload management, and strong security. Users appreciate its ease of use and automation features which support real-time data reporting. The optimizer and intelligent partitioning help improve query speed and efficiency, while multi-temperature data management optimizes data handling.
What are the key features of Teradata?
What benefits and ROI do users look for?
In the finance, retail, and government sectors, Teradata is employed for data warehousing, business intelligence, and analytical processing. It handles vast datasets for activities like customer behavior modeling and enterprise data integration. Supporting efficient reporting and analytics, Teradata enhances data storage and processing, whether deployed on-premise or on cloud platforms.
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