Kovair Data Lake vs Teradata comparison

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87% willing to recommend

Kovair Data Lake

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Executive SummaryUpdated on Oct 6, 2024

Teradata and Kovair Data Lake compete in data management, offering unique strengths. Teradata seems to have the upper hand in deployment and customer service, while Kovair Data Lake leads in advanced features.

Features: Teradata impresses with its scalability, integration capabilities, and reliable performance. It enhances user experience by boosting system efficiency. Kovair Data Lake provides a unified platform with advanced analytics, real-time processing, and a simplified data management approach. Its innovative features enable comprehensive data handling.

Room for Improvement: Teradata could improve its adaptability to new technologies, enhance analytics tools, and offer advanced data insights. Kovair Data Lake would benefit from more intuitive navigation, streamlined data merging processes, and addressing occasional user challenges for an improved experience.

Ease of Deployment and Customer Service: Teradata is known for straightforward deployment and responsive customer service, ensuring a smooth setup. Kovair Data Lake provides flexible deployment but requires more proactive customer support for seamless user onboarding.

Pricing and ROI: Teradata offers cost-effective solutions with a justified ROI, appealing to budget-conscious users. Despite higher initial costs, Kovair Data Lake promises significant ROI through its feature-rich platform, providing long-term value through its comprehensive solutions.

To learn more, read our detailed Kovair Data Lake vs. Teradata Report (Updated: December 2024).

Kovair Data Lake vs. Teradata

December 2024

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Categories and Ranking

Kovair Data Lake

Ranking in Data Warehouse

18th

Average Rating

8.0

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Teradata

Ranking in Data Warehouse

3rd

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (5th), Backup and Recovery (19th), Data Integration (18th), Relational Databases Tools (7th), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of December 2024, in the Data Warehouse category, the mindshare of Kovair Data Lake is 0.4%, up from 0.2% compared to the previous year. The mindshare of Teradata is 17.1%, up from 14.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse

Featured Reviews

LuizKazan

Head of Solutions at Embratel

Ability to interact with teachers in real-time and manage lessons after class

The deployment process is very fast. We have prepared the product to be easily installed, and we have had successful cases where it could be implemented in less than a few weeks. Moreover, Around three or four people in a call center are involved in maintaining the solution. We have a project manager, a service manager, and at least two or three system analysts who handle the maintenance. If there are any issues, we can open a support ticket for them to address.

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SurjitChoudhury

Data engineer at Cocos pt

Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities

We created and constructed the warehouse. We used multiple loading processes like MultiLoad, FastLoad, and Teradata Pump. But those are loading processes, and Teradata is a powerful tool because if we consider older technologies, its architecture with nodes, virtual processes, and nodes is a unique concept. Later, other technologies like Informatica also adopted the concept of nodes from Informatica PowerCenter version 7.x. Previously, it was a client-server architecture, but later, it changed to the nodes concept. Like, we can have the database available 24/7, 365 days. If one node fails, other nodes can take care of it. Informatica adopted all those concepts when it changed its architecture. Even Oracle databases have since adapted their architecture to them. However, this particular Teradata company initially started with its own different type of architecture, which major companies later adopted. It has grown now, but initially, whatever query we sent it would be mapped into a particular component. After that, it goes to the virtual processor and down to the disk, where the actual physical data is loaded. So, in between, there's a map, which acts like a data dictionary. It also holds information about each piece of data, where it's loaded, and on which particular virtual processor or node the data resides. Because Teradata comes with a four-node architecture, or however many nodes we choose, the cost is determined by that initially. So, what type of data does each and every node hold? It's a shared-no architecture. So, whatever task is given to a virtual processor it will be processed. If there's a failure, then it will be taken care of by another virtual processor. Moreover, this solution has impacted the query time and data performance. In Teradata, there's a lot of joining, partitioning, and indexing of records. There are primary and secondary indexes, hash indexing, and other indexing processes. To improve query performance, we first analyze the query and tune it. If a join needs a secondary index, which plays a major role in filtering records, we might reconstruct that particular table with the secondary index. This tuning involves partitioning and indexing. We use these tools and technologies to fine-tune performance. When it comes to integration, tools like Informatica seamlessly connect with Teradata. We ensure the Teradata database is configured correctly in Informatica, including the proper hostname and properties for the load process. We didn't find any major complexity or issues with integration. But, these technologies are quite old now. With newer big data technologies, we've worked with a four-layer architecture, pulling data from Hadoop Lake to Teradata. We configure Teradata with the appropriate hostname and credentials, and use BTEQ queries to load data. Previously, we converted the data warehouse to a CLD model as per Teradata's standardized procedures, moving from an ETL to an EMT process. This allowed us to perform gap analysis on missing entities based on the model and retrieve them from the source system again. We found Teradata integration straightforward and compatible with other tools.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The most valuable feature is the ability to interact with teachers in real-time and manage lessons after class."

"The tool's most valuable features for us are its combination of formatting, ETL, analytics, and storage capabilities."

"It has reduced a lot of reworking on maintaining indexes, partitions, etc."

"The flexibility in design is very good."

"It's very mature from a technology perspective."

"Teradata can be easily used in ETL mode transformations, so there is no need for expensive and inconvenient ETL tools"

"The product's scalability is great. Scalability-wise, I rate the solution a ten out of ten."

"I found all parts --loading, transformation, processing & querying work in parallel, and end-to-end-- to be valuable."

"The most valuable feature is the ease of running queries."

"It has massive parallel processing ability to do large amounts of concurrent querying."

More Teradata pros

Cons

"Maybe the chat conversation feature could be improved."

"The solution is expensive. For future releases, it would be beneficial if Kovair Data Lake could enhance its ETL and data capabilities."

"I would like more security and speed."

"I think the UI is not there yet. It could be improved by being more user-friendly."

"Teradata is an expensive tool. Like, if you're already using Microsoft products like Windows, they'll market all their products together. And with the rise of cloud technologies, companies will adopt solutions that offer them some privileges or facilities. Similar to how SAP does it in the market, so do Microsoft and other companies. Even Oracle and other such tools are quite commonly seen compared to Teradata's competitors in everyday solutions."

"I've been using the same UI for 20 years in Teradata. It could use some updating. Adding more stability around Teradata Studio would be outstanding. Teradata Studio is a Java-based version of their tool. It's much better now, but it still has some room for improvement."

"The reporting side wasn't very good in the past, but with the latest versions, it's getting better. Still, the friendliness of the PDC reporting and functionality needs to be improved."

"We tried to use case Teradata for a data warehouse system, but we had some problems in relation to the Teradata system, CDC tools, and source databases. We were unable to transfer data from HPE Integrity mainframe to Teradata."

"If I want to implement an upgrade, I'd like to see how it will be different. Ideally, Data Lab should help me test production items and also do future things. Future releases should be downloadable and testable in Data Lab."

"The solution could improve by having a cloud version or a cloud component. We have to use other solutions, such as Amazon AWS, Microsoft Azure, or Snowflake for the cloud."

More Teradata cons

Pricing and Cost Advice

"I rate the tool's pricing a five out of ten."

"Teradata is currently making improvements in this area."

"In the past, it turned out that other solutions, in order to provide the full range of abilities that the Teradata platform provides plus the migration costs, would end up costing more than Teradata does."

"Teradata pricing is fine, and it's competitive with all the legacy models. On a scale of one to five, with one being the worst and five being the best, I'm giving Teradata a three, because it can be a little expensive, when compared to other solutions."

"The price of the solution could be reduced, it is expensive."

"The product cost is high for what the client gets. There may be more cost-effective solutions for small and medium-sized organizations."

"The price needs to be more competitive as Hadoop, Redshift, Snowflake, etc are constantly making way into EDW space."

"The initial cost may seem high, but the TCO is low."

"I rate the product price a nine on a scale of one to ten, where one is cheap and ten is expensive."

More Teradata pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Data Warehouse solutions are best for your needs.

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Comparison Review

it_user232068

Senior Data Architect at a pharma/biotech company with 1,001-5,000 employees

Aug 5, 2015

Netezza vs. Teradata

Original published at https://www.linkedin.com/pulse/should-i-choose-net Two leading Massively Parallel Processing (MPP) architectures for Data Warehousing (DW) are IBM PureData System for Analytics (formerly Netezza) and Teradata. I thought talking about the similarities and differences…

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

26%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Kovair Data Lake?

The tool's most valuable features for us are its combination of formatting, ETL, analytics, and storage capabilities.

What needs improvement with Kovair Data Lake?

The solution is expensive. For future releases, it would be beneficial if Kovair Data Lake could enhance its ETL and data capabilities.

What is your primary use case for Kovair Data Lake?

I primarily use Kovair Data Lake for data analytics use cases. This involves data cleansing and gaining business intelligence.

Comparing Teradata and Oracle Database, which product do you think is better and why?

I have spoken to my colleagues about this comparison and in our collective opinion, the reason why some people may declare Teradata better than Oracle is the pricing. Both solutions are quite simi...

Which companies use Teradata and who is it most suitable for?

Before my organization implemented this solution, we researched which big brands were using Teradata, so we knew if it would be compatible with our field. According to the product's site, the comp...

Is Teradata a difficult solution to work with?

Teradata is not a difficult product to work with, especially since they offer you technical support at all levels if you just ask. There are some features that may cause difficulties - for example,...

Oracle Exadata vs Teradata

Comparisons

No data available

Compared 14% of the time

SQL Server vs Teradata

Compared 13% of the time

Snowflake vs Teradata

Compared 8% of the time

MySQL vs Teradata

Compared 8% of the time

Vertica vs Teradata

Compared 5% of the time

More Teradata Competitors

Product Reports

Download Kovair Data Lake product report

Data Warehouse

November 2024

Download Teradata product report

November 2024

Also Known As

No data available

IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture

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Kovair

Overview

Kovair Data Lake is a central database that comes with SQL server support. This makes it capable of storing data from multiple projects residing in diversified tools used by an organization. Based on organizational needs, the stored data is then segregated by departments or business units. Kovair Data Lake also comes with a very intuitive UI interface for managing and monitoring of the Data Lake.

Many organizations use enterprise data warehouses to meet both operational and reporting needs. However, apart from offering a storage and management facilities, there are certain limitations that organizations continue to face. These are –

- Real-time synchronization of data within a centralized data storage

- Traceability and governance of stored data

- Low-cost storage infrastructure compared to Big Data or Data Warehouse

- Handling of low volume but highly diversified data

- Prescriptive analytics that will aid in taking data-driven decisions and on-time service delivery

Kovair has been a market leader in the domain of data integration with a marquee of clients from networking, semiconductor, telecom, manufacturing, banking and finance. Over the recent years, it has witnessed a shift in focus for organizations using multiple tools and different teams. While Kovair Omnibus provides the support for features like traceability, cross tool reporting, and task-based workflow that is simply not enough! Customers today are looking for central data store where data coming from different tools used in an organization could be accumulated in its native format.

Data Lake presents a low-cost alternative to exploding storage and processing costs of traditional warehouses.

While traditional data warehouses store data in hierarchical format. Data Lake offers a central database repository with a flat architecture for storing the data. This protects the data from unwanted manipulation, enabling businesses to take informed decisions accurately and building a better business-customer relationship.

Product Highlights:

- Large Data Repository for Central Administration

- Tool Extractors with WS/SQL Communication Support

- Web-based Data Lake Portal

More details - https://www.kovair.com/data-lake/

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?

Linear Scalability: Easily expands data processing capabilities to handle increasing data loads without performance degradation.
Advanced Analytics: Supports complex analytical operations integrating machine learning and AI for predictive insights.
SQL Compatibility: Offers a comprehensive SQL interface that supports complex queries across diverse data types.
Data Security: Implements rigorous security protocols to protect data integrity and confidentiality.

What benefits and ROI should users look for?

Improved Decision-Making: Derive actionable insights quickly for strategic business decisions.
Cost Efficiency: Optimized resource usage reduces operational costs associated with data processing.
Increased Productivity: Streamlined data operations save time, allowing teams to focus on analysis.
Enhanced Scalability: Seamless growth without significant additional investment as data volumes increase.

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.

Sample Customers

HSBC, NVIDIA, APPLIED MATERIALS, Allscripts, CISCO, Honeywell

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