Kovair Data Lake vs Teradata comparison

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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: October 2024).

Kovair Data Lake vs. Teradata

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Helped 814,763 peers since 2012

Categories and Ranking

Kovair Data Lake

Ranking in Data Warehouse

18th

Average Rating

8.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Teradata

Ranking in Data Warehouse

3rd

Average Rating

8.2

Number of Reviews

Ranking in other categories

Customer Experience Management (3rd), Backup and Recovery (20th), Data Integration (17th), Relational Databases Tools (7th), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of November 2024, in the Data Warehouse category, the mindshare of Kovair Data Lake is 0.4%, up from 0.1% compared to the previous year. The mindshare of Teradata is 17.1%, up from 14.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse

Featured Reviews

LuizKazan

Head of Solutions at Embratel

Jun 27, 2023

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

I have three customers here in Brazil who use Kovair Data Lake in smart classrooms. They use this solution to develop a centralized environment for students The most valuable feature is the ability to interact with teachers in real-time and manage lessons after class. It provides almost unlimited…

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SurjitChoudhury

Data engineer at Cocos pt

Feb 20, 2024

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."

"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."

"The tool's most valuable feature is the warehousing model."

"Viewpoint, the detailed query logs and performance statistics are valuable features."

"I've never had any issues with scalability."

"The product is reliable."

"Teradata's capabilities enhance data management efficiency, support scalability, and contribute to faster query performance."

"The functionality of the solution is excellent."

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

More Teradata pros

Cons

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

"Maybe the chat conversation feature could be improved."

"I would like to see more integration with many different types of data."

"Teradata's pricing is quite high compared to Redshift, Synapse, or GCP alternatives."

"Teradata should focus on functionality for building predictive models because, in that regard, it can definitely improve."

"Stability-wise, we have had some issues with automation and the ability to handle large datasets."

"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."

"The cost of Teradata Cloud Data Warehouse has room for improvement."

"Their level of technical support is adequate. It could be better."

"Teradata has a few AI models, but in data science, we need more flexibility."

More Teradata cons

Pricing and Cost Advice

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

"The price of Teradata is expensive. However, what they deliver they are outstanding. If you're looking for an inexpensive solution to run a database, this isn't your tool. It's the Ferrari of databases for data warehousing."

"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."

"We had a lot of parties involved when purchasing from the AWS Marketplace. They are very flexible and aggressive in trying to close the deal. They are good at what they have to offer and listening to the customer. It's a two-way street."

"The price of Teradata could be less expensive."

"Teradata is expensive, so it's typically marketed to big customers. However, there have been some changes, and Teradata is now offering more flexible pricing models and equipment leasing. They've added pay-as-you-go and cloud models, so it's changing, but Teradata is generally known as an expensive high-end product."

"The cost is significantly high."

"It comes at a notably high cost for what it offers."

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

More Teradata pricing and cost advice

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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

25%

Computer Software Company

10%

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

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SQL Server vs Teradata

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Snowflake vs Teradata

Compared 9% of the time

MySQL vs Teradata

Compared 8% of the time

Vertica vs Teradata

Compared 5% of the time

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Product Reports

Data Warehouse

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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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Kovair Data Lake vs. Teradata