Teradata and Amazon EMR are direct competitors in the data management and big data analytics space. Teradata has the upper hand in robust parallel processing and analytics, while Amazon EMR stands out for its cloud integration and flexibility with AWS services.
Features: Teradata is known for its powerful parallel processing capabilities, reliable architecture, and extensive analytics options suitable for complex tasks. It incorporates features like fast query execution, a highly scalable and robust environment, and comprehensive solutions for in-database analytics and workload management. On the other hand, Amazon EMR benefits significantly from seamless integration with AWS services, providing a highly scalable managed environment that supports multiple frameworks like Hadoop, Spark, and Hive. It is appreciated for easy cluster resizing and flexible deployment options.
Room for Improvement: Teradata users often point out the need for better transactional processing and improved cloud integration, alongside more competitive and flexible pricing options. Amazon EMR users emphasize the need for better cost management, more effective monitoring tools, and quicker startup times, as well as enhanced service integration and debugging potential.
Ease of Deployment and Customer Service: Teradata primarily supports on-premises and hybrid deployments and offers reliable technical support, although some users report delays. For Amazon EMR, which is mainly cloud-based, AWS's infrastructure allows easy scaling and deployment. Its customer service is highly appreciated for being consistent and well-integrated across AWS products, offering reliable support for cloud-first strategies.
Pricing and ROI: Teradata is often praised for its performance but comes at a high cost, which users justify with its superior capabilities and potential ROI. Conversely, Amazon EMR is recognized for its flexible pay-as-you-go pricing model which accommodates dynamic usage, making it cost-efficient and attractive for those seeking scalable cloud solutions.
At least fifteen to twenty percent of our time has been saved using Teradata, which has positively affected team productivity and business outcomes.
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%.
They help with billing, cost determination, IAM properties, security compliance, and deployment and migration activities.
We get all call support, screen sharing support, and immediate support, so there are no problems.
The customer support for Teradata has been great.
The technical support from Teradata is quite advanced.
Customer support is very good, rated eight out of ten under our essential agreement.
Scalability can be provisioned using the auto-scaling feature, EC2 instances, on-demand instances, and storage locations like block storage, S3, or file storage.
Whenever we need more resources, we can add that in Teradata, and when not needed, we can scale it down as well.
This expansion can occur without incurring downtime or taking systems offline.
Teradata's scalability is great; it's been awesome.
Regular updates, patch installations, monitoring, logging, alerting, and disaster recovery activities are crucial for maintaining stability.
The workload management and software maturity provide a reliable system.
I find the stability to be almost a ten out of ten.
The cost factor differs significantly. When you run Spark application on EKS, you run at the pod level, so you can control the compute cost. But in Amazon EMR, when you have to run one application, you have to launch the entire EC2.
There is room for improvement with respect to retries, handling the volume of data on S3 buckets, cluster provisioning, scaling, termination, security, and integration between services like S3, Glue, Lake Formation, and DynamoDB.
If the same thing were available in a web interface, that would be really helpful.
If Teradata could provide a list of certified experts, that would be fantastic.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
Cost optimization can be achieved through instance usage, cluster sharing, and auto-scaling.
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.
We spent roughly $295,000 on setup costs.
Amazon EMR helps in scalability, real-time and batch processing of data, handling efficient data sources, and managing data lakes, data stores, and data marts on file systems and in S3 buckets.
Amazon EMR provides out-of-the-box solutions with Spark and Hive.
It has resulted in better performance improvement within our team as we now cover nine business units instead of 18, thanks to the data performance, which has increased data visibility and helped the enterprise achieve a higher rate of internal return on financials.
The first thing that I appreciate about Teradata is its multi-parallel processing. Whatever queries we execute on Teradata, they are blazingly fast, so it offers really fast connectivity.
The data mover is valuable over the last two years as it allows us to achieve data replication to our disaster recovery systems.
| Product | Market Share (%) |
|---|---|
| Teradata | 8.5% |
| Amazon EMR | 3.3% |
| Other | 88.2% |
| Company Size | Count |
|---|---|
| Small Business | 6 |
| Midsize Enterprise | 5 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 26 |
| Midsize Enterprise | 12 |
| Large Enterprise | 50 |
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?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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